reproducibilityindex.ai

Conference on Neural Information Processing Systems (NeurIPS) - 2021

Conference Proceedings:

Key: PC - Pseudocode, OSC - Open Source Code, OSD - Open Datasets, DS - Dataset Splits, HS - Hardware Specification, SD - Software Dependencies, ES - Experiment Setup

$(\textrm{Implicit})^2$: Implicit Layers for Implicit Representations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
$\alpha$-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
$\texttt{LeadCache}$: Regret-Optimal Caching in Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
(Almost) Free Incentivized Exploration from Decentralized Learning Agents ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
3D Pose Transfer with Correspondence Learning and Mesh Refinement ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
3D Siamese Voxel-to-BEV Tracker for Sparse Point Clouds ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
3DP3: 3D Scene Perception via Probabilistic Programming ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
A 3D Generative Model for Structure-Based Drug Design ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
A Biased Graph Neural Network Sampler with Near-Optimal Regret ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
A Causal Lens for Controllable Text Generation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
A Central Limit Theorem for Differentially Private Query Answering ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
A Comprehensively Tight Analysis of Gradient Descent for PCA ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
A Computationally Efficient Method for Learning Exponential Family Distributions ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
A Constant Approximation Algorithm for Sequential Random-Order No-Substitution k-Median Clustering ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Continuous Mapping For Augmentation Design ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
A Contrastive Learning Approach for Training Variational Autoencoder Priors ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Convergence Analysis of Gradient Descent on Graph Neural Networks ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Faster Decentralized Algorithm for Nonconvex Minimax Problems ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
A Faster Maximum Cardinality Matching Algorithm with Applications in Machine Learning ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
A Framework to Learn with Interpretation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Gang of Adversarial Bandits ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
A Geometric Analysis of Neural Collapse with Unconstrained Features ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A Gradient Method for Multilevel Optimization ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression ✅ ✅ ❌ ✅ ❌ ❌ ✅ 4
A Kernel-based Test of Independence for Cluster-correlated Data ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
A Mathematical Framework for Quantifying Transferability in Multi-source Transfer Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Max-Min Entropy Framework for Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
A Minimalist Approach to Offline Reinforcement Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
A Multi-Implicit Neural Representation for Fonts ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
A No-go Theorem for Robust Acceleration in the Hyperbolic Plane ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A Non-commutative Extension of Lee-Seung's Algorithm for Positive Semidefinite Factorizations ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
A Normative and Biologically Plausible Algorithm for Independent Component Analysis ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
A Note on Sparse Generalized Eigenvalue Problem ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
A PAC-Bayes Analysis of Adversarial Robustness ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
A Prototype-Oriented Framework for Unsupervised Domain Adaptation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Provably Efficient Sample Collection Strategy for Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
A Regression Approach to Learning-Augmented Online Algorithms ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
A Stochastic Newton Algorithm for Distributed Convex Optimization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
A Surrogate Objective Framework for Prediction+Programming with Soft Constraints ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Theoretical Analysis of Fine-tuning with Linear Teachers ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
A Topological Perspective on Causal Inference ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
A Unified Approach to Fair Online Learning via Blackwell Approachability ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Unified View of cGANs with and without Classifiers ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
A Universal Law of Robustness via Isoperimetry ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
A Variational Perspective on Diffusion-Based Generative Models and Score Matching ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A first-order primal-dual method with adaptivity to local smoothness ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
A flow-based latent state generative model of neural population responses to natural images ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
A generative nonparametric Bayesian model for whole genomes ❌ ✅ ✅ ❌ ❌ ✅ ❌ 3
A mechanistic multi-area recurrent network model of decision-making ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
A nonparametric method for gradual change problems with statistical guarantees ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A novel notion of barycenter for probability distributions based on optimal weak mass transport ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
A sampling-based circuit for optimal decision making ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A single gradient step finds adversarial examples on random two-layers neural networks ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
A unified framework for bandit multiple testing ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
A universal probabilistic spike count model reveals ongoing modulation of neural variability ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
A variational approximate posterior for the deep Wishart process ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
A/B Testing for Recommender Systems in a Two-sided Marketplace ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
A/B/n Testing with Control in the Presence of Subpopulations ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
AC-GC: Lossy Activation Compression with Guaranteed Convergence ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
AFEC: Active Forgetting of Negative Transfer in Continual Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
ATISS: Autoregressive Transformers for Indoor Scene Synthesis ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Absolute Neighbour Difference based Correlation Test for Detecting Heteroscedastic Relationships ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Accelerating Quadratic Optimization with Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Accumulative Poisoning Attacks on Real-time Data ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Accurate Point Cloud Registration with Robust Optimal Transport ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Accurately Solving Rod Dynamics with Graph Learning ✅ ✅ ❌ ✅ ✅ ❌ ✅ 5
Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Across-animal odor decoding by probabilistic manifold alignment ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Action-guided 3D Human Motion Prediction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Activation Sharing with Asymmetric Paths Solves Weight Transport Problem without Bidirectional Connection ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Active 3D Shape Reconstruction from Vision and Touch ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Active Learning of Convex Halfspaces on Graphs ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Active Offline Policy Selection ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Active clustering for labeling training data ❌ ❌ ❌ ❌ ❌ ✅ ❌ 1
Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Adaptable Agent Populations via a Generative Model of Policies ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Adapting to function difficulty and growth conditions in private optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Adaptive Conformal Inference Under Distribution Shift ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Adaptive Data Augmentation on Temporal Graphs ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Adaptive Denoising via GainTuning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Adaptive Diffusion in Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Adaptive Machine Unlearning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Adaptive Online Packing-guided Search for POMDPs ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Adaptive Proximal Gradient Methods for Structured Neural Networks ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Adaptive Risk Minimization: Learning to Adapt to Domain Shift ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Adaptive Sampling for Minimax Fair Classification ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Adaptive wavelet distillation from neural networks through interpretations ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Adder Attention for Vision Transformer ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Adjusting for Autocorrelated Errors in Neural Networks for Time Series ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Adversarial Attack Generation Empowered by Min-Max Optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Adversarial Examples Make Strong Poisons ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Adversarial Examples in Multi-Layer Random ReLU Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Adversarial Feature Desensitization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Adversarial Graph Augmentation to Improve Graph Contrastive Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Adversarial Intrinsic Motivation for Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Adversarial Neuron Pruning Purifies Backdoored Deep Models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Adversarial Regression with Doubly Non-negative Weighting Matrices ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Adversarial Reweighting for Partial Domain Adaptation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Adversarial Robustness of Streaming Algorithms through Importance Sampling ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Adversarial Robustness with Non-uniform Perturbations ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Adversarial Robustness with Semi-Infinite Constrained Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Adversarial Teacher-Student Representation Learning for Domain Generalization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Adversarial Training Helps Transfer Learning via Better Representations ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Adversarially Robust Change Point Detection ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Adversarially robust learning for security-constrained optimal power flow ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
Agent Modelling under Partial Observability for Deep Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Algorithmic Instabilities of Accelerated Gradient Descent ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Algorithmic stability and generalization of an unsupervised feature selection algorithm ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Alias-Free Generative Adversarial Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Aligned Structured Sparsity Learning for Efficient Image Super-Resolution ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Aligning Pretraining for Detection via Object-Level Contrastive Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Recovery ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Alignment Attention by Matching Key and Query Distributions ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
All Tokens Matter: Token Labeling for Training Better Vision Transformers ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate ❌ ❌ ❌ ✅ ✅ ❌ ✅ 3
Amortized Variational Inference for Simple Hierarchical Models ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
An Empirical Study of Adder Neural Networks for Object Detection ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
An Exact Characterization of the Generalization Error for the Gibbs Algorithm ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
An Image is Worth More Than a Thousand Words: Towards Disentanglement in The Wild ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
An Improved Analysis of Gradient Tracking for Decentralized Machine Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
An Information-theoretic Approach to Distribution Shifts ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
An Uncertainty Principle is a Price of Privacy-Preserving Microdata ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
An analysis of Ermakov-Zolotukhin quadrature using kernels ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
An online passive-aggressive algorithm for difference-of-squares classification ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Analysis of Sensing Spectral for Signal Recovery under a Generalized Linear Model ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Analysis of one-hidden-layer neural networks via the resolvent method ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Analytic Insights into Structure and Rank of Neural Network Hessian Maps ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Analyzing the Generalization Capability of SGLD Using Properties of Gaussian Channels ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Answering Complex Causal Queries With the Maximum Causal Set Effect ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
Anti-Backdoor Learning: Training Clean Models on Poisoned Data ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Antipodes of Label Differential Privacy: PATE and ALIBI ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Approximate optimization of convex functions with outlier noise ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Approximating the Permanent with Deep Rejection Sampling ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Arbitrary Conditional Distributions with Energy ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Are Transformers more robust than CNNs? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Artistic Style Transfer with Internal-external Learning and Contrastive Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Assessing Fairness in the Presence of Missing Data ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Associating Objects with Transformers for Video Object Segmentation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Associative Memories via Predictive Coding ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Asymptotically Best Causal Effect Identification with Multi-Armed Bandits ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Asymptotically Exact Error Characterization of Offline Policy Evaluation with Misspecified Linear Models ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Asymptotics of representation learning in finite Bayesian neural networks ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Asynchronous Decentralized Online Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Asynchronous Decentralized SGD with Quantized and Local Updates ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Asynchronous Stochastic Optimization Robust to Arbitrary Delays ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Attention Approximates Sparse Distributed Memory ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Attention Bottlenecks for Multimodal Fusion ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Attention over Learned Object Embeddings Enables Complex Visual Reasoning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Auditing Black-Box Prediction Models for Data Minimization Compliance ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
AugMax: Adversarial Composition of Random Augmentations for Robust Training ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Augmented Shortcuts for Vision Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
AutoBalance: Optimized Loss Functions for Imbalanced Data ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
AutoGEL: An Automated Graph Neural Network with Explicit Link Information ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
Autobahn: Automorphism-based Graph Neural Nets ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Automated Discovery of Adaptive Attacks on Adversarial Defenses ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Automated Dynamic Mechanism Design ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Automatic Data Augmentation for Generalization in Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Automatic Symmetry Discovery with Lie Algebra Convolutional Network ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Automatic Unsupervised Outlier Model Selection ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Automorphic Equivalence-aware Graph Neural Network ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Autonomous Reinforcement Learning via Subgoal Curricula ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Average-Reward Learning and Planning with Options ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
BARTScore: Evaluating Generated Text as Text Generation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained Domain ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
BCORLE($\lambda$): An Offline Reinforcement Learning and Evaluation Framework for Coupons Allocation in E-commerce Market ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
BNS: Building Network Structures Dynamically for Continual Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Backdoor Attack with Imperceptible Input and Latent Modification ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Backward-Compatible Prediction Updates: A Probabilistic Approach ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Balanced Chamfer Distance as a Comprehensive Metric for Point Cloud Completion ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Bandit Learning with Delayed Impact of Actions ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Bandit Phase Retrieval ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Bandit Quickest Changepoint Detection ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Bandits with Knapsacks beyond the Worst Case ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Bandits with many optimal arms ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Batch Active Learning at Scale ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Batch Normalization Orthogonalizes Representations in Deep Random Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
BatchQuant: Quantized-for-all Architecture Search with Robust Quantizer ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Batched Thompson Sampling ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
BayesIMP: Uncertainty Quantification for Causal Data Fusion ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Bayesian Adaptation for Covariate Shift ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Bayesian Bellman Operators ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Bayesian Optimization of Function Networks ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Bayesian Optimization with High-Dimensional Outputs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Bayesian decision-making under misspecified priors with applications to meta-learning ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Behavior From the Void: Unsupervised Active Pre-Training ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Bellman-consistent Pessimism for Offline Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Beltrami Flow and Neural Diffusion on Graphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Best-case lower bounds in online learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Better Algorithms for Individually Fair $k$-Clustering ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy to Game ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Beyond Bandit Feedback in Online Multiclass Classification ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Beyond the Signs: Nonparametric Tensor Completion via Sign Series ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Bias and variance of the Bayesian-mean decoder ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Biological learning in key-value memory networks ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Black Box Probabilistic Numerics ❌ ✅ ❌ ❌ ❌ ✅ ✅ 3
BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Blending Anti-Aliasing into Vision Transformer ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
BooVAE: Boosting Approach for Continual Learning of VAE ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
BooVI: Provably Efficient Bootstrapped Value Iteration ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Boost Neural Networks by Checkpoints ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Boosted CVaR Classification ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Boosting with Multiple Sources ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Bootstrap Your Object Detector via Mixed Training ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Bootstrapping the Error of Oja's Algorithm ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Bounds all around: training energy-based models with bidirectional bounds ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Breaking the Dilemma of Medical Image-to-image Translation ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Breaking the centralized barrier for cross-device federated learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Bridging the Imitation Gap by Adaptive Insubordination ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Bubblewrap: Online tiling and real-time flow prediction on neural manifolds ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
CAFE: Catastrophic Data Leakage in Vertical Federated Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
CATs: Cost Aggregation Transformers for Visual Correspondence ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
CBP: backpropagation with constraint on weight precision using a pseudo-Lagrange multiplier method ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
CCVS: Context-aware Controllable Video Synthesis ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
CHIP: CHannel Independence-based Pruning for Compact Neural Networks ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
CLIP-It! Language-Guided Video Summarization ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
COHESIV: Contrastive Object and Hand Embedding Segmentation In Video ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
COMBO: Conservative Offline Model-Based Policy Optimization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Calibration and Consistency of Adversarial Surrogate Losses ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Can Information Flows Suggest Targets for Interventions in Neural Circuits? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Can contrastive learning avoid shortcut solutions? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Can fMRI reveal the representation of syntactic structure in the brain? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Can multi-label classification networks know what they don’t know? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Canonical Capsules: Self-Supervised Capsules in Canonical Pose ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Cardinality constrained submodular maximization for random streams ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Cardinality-Regularized Hawkes-Granger Model ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Catch-A-Waveform: Learning to Generate Audio from a Single Short Example ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Causal Abstractions of Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Causal Bandits with Unknown Graph Structure ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Causal Effect Inference for Structured Treatments ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Causal Identification with Matrix Equations ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Causal Inference for Event Pairs in Multivariate Point Processes ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Causal Influence Detection for Improving Efficiency in Reinforcement Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Causal Navigation by Continuous-time Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Celebrating Diversity in Shared Multi-Agent Reinforcement Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Center Smoothing: Certified Robustness for Networks with Structured Outputs ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
CentripetalText: An Efficient Text Instance Representation for Scene Text Detection ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Certifying Robustness to Programmable Data Bias in Decision Trees ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Challenges and Opportunities in High Dimensional Variational Inference ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
Change Point Detection via Multivariate Singular Spectrum Analysis ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Channel Permutations for N:M Sparsity ✅ ✅ ✅ ✅ ✅ ❌ ❌ 5
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Characterizing possible failure modes in physics-informed neural networks ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Characterizing the risk of fairwashing ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Charting and Navigating the Space of Solutions for Recurrent Neural Networks ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Chasing Sparsity in Vision Transformers: An End-to-End Exploration ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Choose a Transformer: Fourier or Galerkin ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Circa: Stochastic ReLUs for Private Deep Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Class-Disentanglement and Applications in Adversarial Detection and Defense ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Class-Incremental Learning via Dual Augmentation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Class-agnostic Reconstruction of Dynamic Objects from Videos ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Clockwork Variational Autoencoders ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Clustering Effect of Adversarial Robust Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Co-evolution Transformer for Protein Contact Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
CoAtNet: Marrying Convolution and Attention for All Data Sizes ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust PointCloud Registration ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Coarse-to-fine Animal Pose and Shape Estimation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Cockpit: A Practical Debugging Tool for the Training of Deep Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
CogView: Mastering Text-to-Image Generation via Transformers ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Collaborating with Humans without Human Data ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Collaborative Causal Discovery with Atomic Interventions ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning) ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Collaborative Uncertainty in Multi-Agent Trajectory Forecasting ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Collapsed Variational Bounds for Bayesian Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Combinatorial Pure Exploration with Bottleneck Reward Function ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Combiner: Full Attention Transformer with Sparse Computation Cost ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Communication-efficient SGD: From Local SGD to One-Shot Averaging ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Compositional Reinforcement Learning from Logical Specifications ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Compositional Transformers for Scene Generation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Comprehensive Knowledge Distillation with Causal Intervention ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Compressed Video Contrastive Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Compressive Visual Representations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Computer-Aided Design as Language ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Concentration inequalities under sub-Gaussian and sub-exponential conditions ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Conditional Generation Using Polynomial Expansions ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Conditioning Sparse Variational Gaussian Processes for Online Decision-making ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Confident Anchor-Induced Multi-Source Free Domain Adaptation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Conflict-Averse Gradient Descent for Multi-task learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Conformal Bayesian Computation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Conformal Prediction using Conditional Histograms ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Conformal Time-series Forecasting ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Conservative Offline Distributional Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Consistency Regularization for Variational Auto-Encoders ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Consistent Non-Parametric Methods for Maximizing Robustness ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Constrained Optimization to Train Neural Networks on Critical and Under-Represented Classes ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Constrained Robust Submodular Partitioning ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Constrained Two-step Look-Ahead Bayesian Optimization ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Container: Context Aggregation Networks ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Contextual Similarity Aggregation with Self-attention for Visual Re-ranking ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Continual Auxiliary Task Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Continual Learning via Local Module Composition ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Continual World: A Robotic Benchmark For Continual Reinforcement Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Continuous Doubly Constrained Batch Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Continuous Latent Process Flows ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Continuous Mean-Covariance Bandits ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Continuous vs. Discrete Optimization of Deep Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Continuous-time edge modelling using non-parametric point processes ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Contrastive Active Inference ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels ❌ ❌ ✅ ❌ ✅ ❌ ❌ 2
Contrastive Laplacian Eigenmaps ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Contrastive Learning for Neural Topic Model ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Contrastive Learning of Global and Local Video Representations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Contrastive Reinforcement Learning of Symbolic Reasoning Domains ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Contrastively Disentangled Sequential Variational Autoencoder ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Control Variates for Slate Off-Policy Evaluation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Controllable and Compositional Generation with Latent-Space Energy-Based Models ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Controlled Text Generation as Continuous Optimization with Multiple Constraints ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Controlling Neural Networks with Rule Representations ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Convergence and Alignment of Gradient Descent with Random Backpropagation Weights ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Convergence of adaptive algorithms for constrained weakly convex optimization ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Convex Polytope Trees ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Convex-Concave Min-Max Stackelberg Games ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Coordinated Proximal Policy Optimization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Coresets for Classification – Simplified and Strengthened ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Coresets for Clustering with Missing Values ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Coresets for Decision Trees of Signals ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Coresets for Time Series Clustering ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Corruption Robust Active Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Cortico-cerebellar networks as decoupling neural interfaces ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Counterbalancing Learning and Strategic Incentives in Allocation Markets ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Counterexample Guided RL Policy Refinement Using Bayesian Optimization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Counterfactual Explanations Can Be Manipulated ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Counterfactual Explanations in Sequential Decision Making Under Uncertainty ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Counterfactual Invariance to Spurious Correlations in Text Classification ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Counterfactual Maximum Likelihood Estimation for Training Deep Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Coupled Gradient Estimators for Discrete Latent Variables ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Coupled Segmentation and Edge Learning via Dynamic Graph Propagation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Credal Self-Supervised Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Credit Assignment Through Broadcasting a Global Error Vector ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Credit Assignment in Neural Networks through Deep Feedback Control ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Cross-view Geo-localization with Layer-to-Layer Transformer ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
CrypTen: Secure Multi-Party Computation Meets Machine Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Curriculum Design for Teaching via Demonstrations: Theory and Applications ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Curriculum Disentangled Recommendation with Noisy Multi-feedback ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Curriculum Learning for Vision-and-Language Navigation ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Curriculum Offline Imitating Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Cycle Self-Training for Domain Adaptation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
DOBF: A Deobfuscation Pre-Training Objective for Programming Languages ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
DOCTOR: A Simple Method for Detecting Misclassification Errors ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
DRIVE: One-bit Distributed Mean Estimation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
DRONE: Data-aware Low-rank Compression for Large NLP Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Dangers of Bayesian Model Averaging under Covariate Shift ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Data Augmentation Can Improve Robustness ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Data Sharing and Compression for Cooperative Networked Control ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Data driven semi-supervised learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Data-Efficient Instance Generation from Instance Discrimination ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Dataset Distillation with Infinitely Wide Convolutional Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
De-randomizing MCMC dynamics with the diffusion Stein operator ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Debiased Visual Question Answering from Feature and Sample Perspectives ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Decentralized Learning in Online Queuing Systems ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Decentralized Q-learning in Zero-sum Markov Games ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
Decision Transformer: Reinforcement Learning via Sequence Modeling ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Deconditional Downscaling with Gaussian Processes ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Deconvolutional Networks on Graph Data ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Decoupling the Depth and Scope of Graph Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Deep Conditional Gaussian Mixture Model for Constrained Clustering ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Deep Contextual Video Compression ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Deep Explicit Duration Switching Models for Time Series ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Deep Extended Hazard Models for Survival Analysis ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Deep Extrapolation for Attribute-Enhanced Generation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Deep Learning Through the Lens of Example Difficulty ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Deep Learning on a Data Diet: Finding Important Examples Early in Training ❌ ❌ ✅ ✅ ❌ ✅ ✅ 4
Deep Learning with Label Differential Privacy ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Deep Markov Factor Analysis: Towards Concurrent Temporal and Spatial Analysis of fMRI Data ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Deep Molecular Representation Learning via Fusing Physical and Chemical Information ❌ ❌ ✅ ✅ ❌ ✅ ✅ 4
Deep Networks Provably Classify Data on Curves ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Deep Neural Networks as Point Estimates for Deep Gaussian Processes ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Deep Reinforcement Learning at the Edge of the Statistical Precipice ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Deep Residual Learning in Spiking Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Deep Self-Dissimilarities as Powerful Visual Fingerprints ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Deep Synoptic Monte-Carlo Planning in Reconnaissance Blind Chess ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
DeepGEM: Generalized Expectation-Maximization for Blind Inversion ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
DeepReduce: A Sparse-tensor Communication Framework for Federated Deep Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Deeply Shared Filter Bases for Parameter-Efficient Convolutional Neural Networks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Deformable Butterfly: A Highly Structured and Sparse Linear Transform ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Demystifying and Generalizing BinaryConnect ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Denoising Normalizing Flow ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Dense Keypoints via Multiview Supervision ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Dense Unsupervised Learning for Video Segmentation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Densely connected normalizing flows ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Design of Experiments for Stochastic Contextual Linear Bandits ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Designing Counterfactual Generators using Deep Model Inversion ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Detecting Anomalous Event Sequences with Temporal Point Processes ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Detecting Individual Decision-Making Style: Exploring Behavioral Stylometry in Chess ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Detecting Moments and Highlights in Videos via Natural Language Queries ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
DiBS: Differentiable Bayesian Structure Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Differentiable Learning Under Triage ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Differentiable Multiple Shooting Layers ❌ ❌ ✅ ❌ ✅ ❌ ❌ 2
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Differentiable Quality Diversity ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Differentiable Simulation of Soft Multi-body Systems ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Differentiable Spline Approximations ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Differentiable Synthesis of Program Architectures ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Differentiable Unsupervised Feature Selection based on a Gated Laplacian ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Differentiable rendering with perturbed optimizers ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Differential Privacy Over Riemannian Manifolds ❌ ✅ ❌ ❌ ✅ ❌ ❌ 2
Differentially Private Empirical Risk Minimization under the Fairness Lens ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Differentially Private Federated Bayesian Optimization with Distributed Exploration ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Differentially Private Learning with Adaptive Clipping ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Differentially Private Model Personalization ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Differentially Private Multi-Armed Bandits in the Shuffle Model ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Differentially Private Sampling from Distributions ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Differentially Private n-gram Extraction ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Diffusion Models Beat GANs on Image Synthesis ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Diffusion Normalizing Flow ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Dimension-free empirical entropy estimation ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Dimensionality Reduction for Wasserstein Barycenter ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Direct Multi-view Multi-person 3D Pose Estimation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Directed Graph Contrastive Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Directed Probabilistic Watershed ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Directed Spectrum Measures Improve Latent Network Models Of Neural Populations ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
Directional Message Passing on Molecular Graphs via Synthetic Coordinates ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Discovering and Achieving Goals via World Models ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Discovery of Options via Meta-Learned Subgoals ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Discrete-Valued Neural Communication ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Disentangled Contrastive Learning on Graphs ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Disrupting Deep Uncertainty Estimation Without Harming Accuracy ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Dissecting the Diffusion Process in Linear Graph Convolutional Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Distilling Image Classifiers in Object Detectors ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Distilling Object Detectors with Feature Richness ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Distributed Deep Learning In Open Collaborations ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Distributed Machine Learning with Sparse Heterogeneous Data ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Distributed Principal Component Analysis with Limited Communication ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Distributed Saddle-Point Problems Under Data Similarity ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Distributed Zero-Order Optimization under Adversarial Noise ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Distribution-free inference for regression: discrete, continuous, and in between ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Distributional Reinforcement Learning for Multi-Dimensional Reward Functions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Distributionally Robust Imitation Learning ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Diverse Message Passing for Attribute with Heterophily ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Diversity Matters When Learning From Ensembles ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Do Different Tracking Tasks Require Different Appearance Models? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Do Input Gradients Highlight Discriminative Features? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
Do Transformers Really Perform Badly for Graph Representation? ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Do Vision Transformers See Like Convolutional Neural Networks? ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Do Wider Neural Networks Really Help Adversarial Robustness? ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Does Knowledge Distillation Really Work? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Does Preprocessing Help Training Over-parameterized Neural Networks? ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Does enforcing fairness mitigate biases caused by subpopulation shift? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Domain Invariant Representation Learning with Domain Density Transformations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Double Machine Learning Density Estimation for Local Treatment Effects with Instruments ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Double/Debiased Machine Learning for Dynamic Treatment Effects ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Doubly Robust Thompson Sampling with Linear Payoffs ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Dr Jekyll & Mr Hyde: the strange case of off-policy policy updates ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
Dual Parameterization of Sparse Variational Gaussian Processes ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Dual Progressive Prototype Network for Generalized Zero-Shot Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Dual-stream Network for Visual Recognition ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
DualNet: Continual Learning, Fast and Slow ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Dueling Bandits with Adversarial Sleeping ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Dueling Bandits with Team Comparisons ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Duplex Sequence-to-Sequence Learning for Reversible Machine Translation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Dynamic Analysis of Higher-Order Coordination in Neuronal Assemblies via De-Sparsified Orthogonal Matching Pursuit ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Dynamic Bottleneck for Robust Self-Supervised Exploration ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Dynamic COVID risk assessment accounting for community virus exposure from a spatial-temporal transmission model ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Dynamic Causal Bayesian Optimization ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Dynamic Grained Encoder for Vision Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Dynamic Inference with Neural Interpreters ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Dynamic Normalization and Relay for Video Action Recognition ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Dynamic Resolution Network ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Dynamic Trace Estimation ✅ ❌ ✅ ❌ ❌ ✅ ❌ 3
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Dynamic influence maximization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Dynamic population-based meta-learning for multi-agent communication with natural language ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Dynamical Wasserstein Barycenters for Time-series Modeling ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Dynamics-regulated kinematic policy for egocentric pose estimation ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
E(n) Equivariant Normalizing Flows ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
EDGE: Explaining Deep Reinforcement Learning Policies ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
EIGNN: Efficient Infinite-Depth Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
ELLA: Exploration through Learned Language Abstraction ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Early Convolutions Help Transformers See Better ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Early-stopped neural networks are consistent ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Edge Representation Learning with Hypergraphs ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
EditGAN: High-Precision Semantic Image Editing ❌ ❌ ✅ ❌ ✅ ✅ ✅ 4
Editing a classifier by rewriting its prediction rules ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Effective Meta-Regularization by Kernelized Proximal Regularization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Efficient Active Learning for Gaussian Process Classification by Error Reduction ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Efficient Bayesian network structure learning via local Markov boundary search ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Efficient Combination of Rematerialization and Offloading for Training DNNs ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Efficient Equivariant Network ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Efficient Generalization with Distributionally Robust Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Efficient Learning of Discrete-Continuous Computation Graphs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Efficient Neural Network Training via Forward and Backward Propagation Sparsification ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Efficient Online Estimation of Causal Effects by Deciding What to Observe ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Efficient Statistical Assessment of Neural Network Corruption Robustness ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Efficient Training of Retrieval Models using Negative Cache ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Efficient Training of Visual Transformers with Small Datasets ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Efficient Truncated Linear Regression with Unknown Noise Variance ✅ ❌ ✅ ❌ ❌ ✅ ❌ 3
Efficient and Accurate Gradients for Neural SDEs ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Efficient and Local Parallel Random Walks ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Efficient constrained sampling via the mirror-Langevin algorithm ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Efficient methods for Gaussian Markov random fields under sparse linear constraints ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
Efficiently Identifying Task Groupings for Multi-Task Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Efficiently Learning One Hidden Layer ReLU Networks From Queries ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Embedding Principle of Loss Landscape of Deep Neural Networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Emergent Communication of Generalizations ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Emergent Communication under Varying Sizes and Connectivities ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Emergent Discrete Communication in Semantic Spaces ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Encoding Robustness to Image Style via Adversarial Feature Perturbations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Encoding Spatial Distribution of Convolutional Features for Texture Representation ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
End-to-End Weak Supervision ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
End-to-end Multi-modal Video Temporal Grounding ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
End-to-end reconstruction meets data-driven regularization for inverse problems ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Ensembling Graph Predictions for AMR Parsing ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Entropic Desired Dynamics for Intrinsic Control ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Entropy-based adaptive Hamiltonian Monte Carlo ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Environment Generation for Zero-Shot Compositional Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Episodic Multi-agent Reinforcement Learning with Curiosity-driven Exploration ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Equilibrium Refinement for the Age of Machines: The One-Sided Quasi-Perfect Equilibrium ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Equivariant Manifold Flows ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Error Compensated Distributed SGD Can Be Accelerated ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
ErrorCompensatedX: error compensation for variance reduced algorithms ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Escape saddle points by a simple gradient-descent based algorithm ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
Escaping Saddle Points with Compressed SGD ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Estimating High Order Gradients of the Data Distribution by Denoising ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Estimating Multi-cause Treatment Effects via Single-cause Perturbation ✅ ✅ ❌ ✅ ❌ ❌ ✅ 4
Estimating the Long-Term Effects of Novel Treatments ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Estimating the Unique Information of Continuous Variables ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Evaluating Efficient Performance Estimators of Neural Architectures ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Evaluating State-of-the-Art Classification Models Against Bayes Optimality ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Evaluating model performance under worst-case subpopulations ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Even your Teacher Needs Guidance: Ground-Truth Targets Dampen Regularization Imposed by Self-Distillation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Exact marginal prior distributions of finite Bayesian neural networks ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Excess Capacity and Backdoor Poisoning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning ❌ ❌ ✅ ✅ ❌ ✅ ✅ 4
Explaining Hyperparameter Optimization via Partial Dependence Plots ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Explaining Latent Representations with a Corpus of Examples ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Explanation-based Data Augmentation for Image Classification ✅ ❌ ✅ ✅ ✅ ❌ ❌ 4
Explicable Reward Design for Reinforcement Learning Agents ✅ ✅ ❌ ✅ ❌ ❌ ✅ 4
Explicit loss asymptotics in the gradient descent training of neural networks ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
Exploiting Domain-Specific Features to Enhance Domain Generalization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Exploiting Opponents Under Utility Constraints in Sequential Games ✅ ❌ ❌ ❌ ❌ ✅ ✅ 3
Exploiting a Zoo of Checkpoints for Unseen Tasks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Exploring Cross-Video and Cross-Modality Signals for Weakly-Supervised Audio-Visual Video Parsing ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Exploring Forensic Dental Identification with Deep Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Exploring the Limits of Out-of-Distribution Detection ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Exponential Graph is Provably Efficient for Decentralized Deep Training ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Exponential Separation between Two Learning Models and Adversarial Robustness ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Extracting Deformation-Aware Local Features by Learning to Deform ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
FACMAC: Factored Multi-Agent Centralised Policy Gradients ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
FINE Samples for Learning with Noisy Labels ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
FLEX: Unifying Evaluation for Few-Shot NLP ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Fair Algorithms for Multi-Agent Multi-Armed Bandits ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Fair Classification with Adversarial Perturbations ❌ ❌ ✅ ✅ ❌ ✅ ✅ 4
Fair Clustering Under a Bounded Cost ✅ ❌ ✅ ❌ ❌ ✅ ✅ 4
Fair Exploration via Axiomatic Bargaining ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Fair Scheduling for Time-dependent Resources ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Fair Sequential Selection Using Supervised Learning Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Fair Sortition Made Transparent ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Fairness in Ranking under Uncertainty ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Fairness via Representation Neutralization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Fast Abductive Learning by Similarity-based Consistency Optimization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Fast Algorithms for $L_\infty$-constrained S-rectangular Robust MDPs ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Fast Axiomatic Attribution for Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Fast Certified Robust Training with Short Warmup ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Fast Federated Learning in the Presence of Arbitrary Device Unavailability ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Fast Pure Exploration via Frank-Wolfe ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Fast Training Method for Stochastic Compositional Optimization Problems ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Fast Training of Neural Lumigraph Representations using Meta Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Fast and Memory Efficient Differentially Private-SGD via JL Projections ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Fast and accurate randomized algorithms for low-rank tensor decompositions ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Fast rates for prediction with limited expert advice ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Faster Algorithms and Constant Lower Bounds for the Worst-Case Expected Error ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Faster Matchings via Learned Duals ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Faster Neural Network Training with Approximate Tensor Operations ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Faster Non-asymptotic Convergence for Double Q-learning ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Faster proximal algorithms for matrix optimization using Jacobi-based eigenvalue methods ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Federated Graph Classification over Non-IID Graphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Federated Linear Contextual Bandits ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Federated Multi-Task Learning under a Mixture of Distributions ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Federated Reconstruction: Partially Local Federated Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
Federated-EM with heterogeneity mitigation and variance reduction ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Few-Round Learning for Federated Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Few-Shot Data-Driven Algorithms for Low Rank Approximation ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Few-Shot Object Detection via Association and DIscrimination ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Few-Shot Segmentation via Cycle-Consistent Transformer ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Finding Bipartite Components in Hypergraphs ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Fine-Grained Zero-Shot Learning with DNA as Side Information ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Fine-grained Generalization Analysis of Inductive Matrix Completion ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Finite Sample Analysis of Average-Reward TD Learning and $Q$-Learning ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Fitting summary statistics of neural data with a differentiable spiking network simulator ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Flexible Option Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Focal Attention for Long-Range Interactions in Vision Transformers ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Formalizing the Generalization-Forgetting Trade-off in Continual Learning ✅ ✅ ✅ ❌ ✅ ✅ ❌ 5
Forster Decomposition and Learning Halfspaces with Noise ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Foundations of Symbolic Languages for Model Interpretability ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Framing RNN as a kernel method: A neural ODE approach ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
From global to local MDI variable importances for random forests and when they are Shapley values ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Functional Neural Networks for Parametric Image Restoration Problems ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Functional Regularization for Reinforcement Learning via Learned Fourier Features ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Functional Variational Inference based on Stochastic Process Generators ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Fuzzy Clustering with Similarity Queries ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Garment4D: Garment Reconstruction from Point Cloud Sequences ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Gauge Equivariant Transformer ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Gaussian Kernel Mixture Network for Single Image Defocus Deblurring ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
GemNet: Universal Directional Graph Neural Networks for Molecules ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
General Nonlinearities in SO(2)-Equivariant CNNs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Generalizable Imitation Learning from Observation via Inferring Goal Proximity ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Generalizable Multi-linear Attention Network ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generalization Bounds for (Wasserstein) Robust Optimization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Generalization Guarantee of SGD for Pairwise Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Generalized DataWeighting via Class-Level Gradient Manipulation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generalized Linear Bandits with Local Differential Privacy ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Generalized Proximal Policy Optimization with Sample Reuse ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Generalized Shape Metrics on Neural Representations ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Generalized and Discriminative Few-Shot Object Detection via SVD-Dictionary Enhancement ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Generating High-Quality Explanations for Navigation in Partially-Revealed Environments ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Generative Occupancy Fields for 3D Surface-Aware Image Synthesis ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Generative vs. Discriminative: Rethinking The Meta-Continual Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generic Neural Architecture Search via Regression ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Geometry Processing with Neural Fields ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
Glance-and-Gaze Vision Transformer ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Global Convergence of Online Optimization for Nonlinear Model Predictive Control ✅ ✅ ❌ ❌ ❌ ✅ ✅ 4
Global Filter Networks for Image Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Global-aware Beam Search for Neural Abstractive Summarization ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Going Beyond Linear RL: Sample Efficient Neural Function Approximation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Going Beyond Linear Transformers with Recurrent Fast Weight Programmers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Gone Fishing: Neural Active Learning with Fisher Embeddings ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Good Classification Measures and How to Find Them ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Gradient Inversion with Generative Image Prior ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Gradient Starvation: A Learning Proclivity in Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Gradient-based Editing of Memory Examples for Online Task-free Continual Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Gradient-based Hyperparameter Optimization Over Long Horizons ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Gradual Domain Adaptation without Indexed Intermediate Domains ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Grammar-Based Grounded Lexicon Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Graph Adversarial Self-Supervised Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Graph Differentiable Architecture Search with Structure Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Graph Neural Networks with Adaptive Residual ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Graph Neural Networks with Local Graph Parameters ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Graphical Models in Heavy-Tailed Markets ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Grounding Representation Similarity Through Statistical Testing ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Grounding Spatio-Temporal Language with Transformers ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Grounding inductive biases in natural images: invariance stems from variations in data ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Group Equivariant Subsampling ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
HNPE: Leveraging Global Parameters for Neural Posterior Estimation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
HRFormer: High-Resolution Vision Transformer for Dense Predict ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Habitat 2.0: Training Home Assistants to Rearrange their Habitat ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Handling Long-tailed Feature Distribution in AdderNets ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Hard-Attention for Scalable Image Classification ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Hash Layers For Large Sparse Models ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Heavy Ball Momentum for Conditional Gradient ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Heavy Ball Neural Ordinary Differential Equations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Hessian Eigenspectra of More Realistic Nonlinear Models ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Heuristic-Guided Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Hierarchical Clustering: $O(1)$-Approximation for Well-Clustered Graphs ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Hierarchical Reinforcement Learning with Timed Subgoals ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Hierarchical Skills for Efficient Exploration ✅ ✅ ❌ ❌ ✅ ❌ ❌ 3
High Probability Complexity Bounds for Line Search Based on Stochastic Oracles ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes ❌ ✅ ❌ ✅ ❌ ❌ ❌ 2
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
History Aware Multimodal Transformer for Vision-and-Language Navigation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
How Data Augmentation affects Optimization for Linear Regression ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
How Does it Sound? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
How Fine-Tuning Allows for Effective Meta-Learning ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
How Modular should Neural Module Networks Be for Systematic Generalization? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
How Powerful are Performance Predictors in Neural Architecture Search? ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
How Tight Can PAC-Bayes be in the Small Data Regime? ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
How can classical multidimensional scaling go wrong? ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
How to transfer algorithmic reasoning knowledge to learn new algorithms? ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Human-Adversarial Visual Question Answering ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
HyperSPNs: Compact and Expressive Probabilistic Circuits ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Hyperbolic Busemann Learning with Ideal Prototypes ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Hyperbolic Procrustes Analysis Using Riemannian Geometry ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Hypergraph Propagation and Community Selection for Objects Retrieval ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Hyperparameter Optimization Is Deceiving Us, and How to Stop It ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Hyperparameter Tuning is All You Need for LISTA ✅ ✅ ❌ ✅ ❌ ❌ ✅ 4
IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise Encoding ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
IQ-Learn: Inverse soft-Q Learning for Imitation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
IRM—when it works and when it doesn't: A test case of natural language inference ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Identifiability in inverse reinforcement learning ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Identifiable Generative models for Missing Not at Random Data Imputation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Identification and Estimation of Joint Probabilities of Potential Outcomes in Observational Studies with Covariate Information ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Identifying and Benchmarking Natural Out-of-Context Prediction Problems ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Identity testing for Mallows model ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Image Generation using Continuous Filter Atoms ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Imitation with Neural Density Models ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Implicit Generative Copulas ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Implicit Regularization in Matrix Sensing via Mirror Descent ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Implicit SVD for Graph Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Implicit Semantic Response Alignment for Partial Domain Adaptation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Implicit Sparse Regularization: The Impact of Depth and Early Stopping ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Implicit Task-Driven Probability Discrepancy Measure for Unsupervised Domain Adaptation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Implicit Transformer Network for Screen Content Image Continuous Super-Resolution ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Impression learning: Online representation learning with synaptic plasticity ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Improved Regret Bounds for Tracking Experts with Memory ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Improved Regularization and Robustness for Fine-tuning in Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Improved Transformer for High-Resolution GANs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Improving Calibration through the Relationship with Adversarial Robustness ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Improving Compositionality of Neural Networks by Decoding Representations to Inputs ❌ ❌ ✅ ❌ ✅ ✅ ✅ 4
Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Improving Conditional Coverage via Orthogonal Quantile Regression ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Improving Contrastive Learning on Imbalanced Data via Open-World Sampling ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Improving Deep Learning Interpretability by Saliency Guided Training ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
Improving Robustness using Generated Data ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Improving Transferability of Representations via Augmentation-Aware Self-Supervision ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Improving black-box optimization in VAE latent space using decoder uncertainty ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Increasing Liquid State Machine Performance with Edge-of-Chaos Dynamics Organized by Astrocyte-modulated Plasticity ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Independent Prototype Propagation for Zero-Shot Compositionality ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Independent mechanism analysis, a new concept? ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Indexed Minimum Empirical Divergence for Unimodal Bandits ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Individual Privacy Accounting via a Rényi Filter ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Infinite Time Horizon Safety of Bayesian Neural Networks ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Influence Patterns for Explaining Information Flow in BERT ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
InfoGCL: Information-Aware Graph Contrastive Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Information Directed Reward Learning for Reinforcement Learning ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Information Directed Sampling for Sparse Linear Bandits ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Information is Power: Intrinsic Control via Information Capture ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Information-constrained optimization: can adaptive processing of gradients help? ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Information-theoretic generalization bounds for black-box learning algorithms ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Instance-Conditional Knowledge Distillation for Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Instance-Conditioned GAN ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Instance-Dependent Partial Label Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Instance-dependent Label-noise Learning under a Structural Causal Model ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Instance-optimal Mean Estimation Under Differential Privacy ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Integrated Latent Heterogeneity and Invariance Learning in Kernel Space ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Integrating Tree Path in Transformer for Code Representation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Interactive Label Cleaning with Example-based Explanations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Interpolation can hurt robust generalization even when there is no noise ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Interpretable agent communication from scratch (with a generic visual processor emerging on the side) ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Intriguing Properties of Contrastive Losses ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Intriguing Properties of Vision Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Introspective Distillation for Robust Question Answering ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Invariant Causal Imitation Learning for Generalizable Policies ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Inverse Problems Leveraging Pre-trained Contrastive Representations ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
Inverse-Weighted Survival Games ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Invertible DenseNets with Concatenated LipSwish ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression: A Statistical Mechanics Analysis ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Iterative Amortized Policy Optimization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias ✅ ✅ ❌ ❌ ✅ ❌ ❌ 3
Iterative Connecting Probability Estimation for Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Iterative Teacher-Aware Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Iterative Teaching by Label Synthesis ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate ✅ ❌ ❌ ❌ ✅ ✅ ✅ 4
Joint Inference for Neural Network Depth and Dropout Regularization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Joint Modeling of Visual Objects and Relations for Scene Graph Generation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Joint inference and input optimization in equilibrium networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
K-Net: Towards Unified Image Segmentation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
K-level Reasoning for Zero-Shot Coordination in Hanabi ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural Network ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Kernel Functional Optimisation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Kernel Identification Through Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Knowledge-Adaptation Priors ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Knowledge-inspired 3D Scene Graph Prediction in Point Cloud ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
LEADS: Learning Dynamical Systems that Generalize Across Environments ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
LSH-SMILE: Locality Sensitive Hashing Accelerated Simulation and Learning ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Label Disentanglement in Partition-based Extreme Multilabel Classification ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Label Noise SGD Provably Prefers Flat Global Minimizers ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Label consistency in overfitted generalized $k$-means ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Label-Imbalanced and Group-Sensitive Classification under Overparameterization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Landscape analysis of an improved power method for tensor decomposition ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Language models enable zero-shot prediction of the effects of mutations on protein function ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Laplace Redux - Effortless Bayesian Deep Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Large-Scale Learning with Fourier Features and Tensor Decompositions ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Large-Scale Unsupervised Object Discovery ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Large-Scale Wasserstein Gradient Flows ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Last iterate convergence of SGD for Least-Squares in the Interpolation regime. ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Last-iterate Convergence in Extensive-Form Games ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Latent Matters: Learning Deep State-Space Models ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Lattice partition recovery with dyadic CART ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Learnability of Linear Thresholds from Label Proportions ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection ✅ ✅ ✅ ✅ ✅ ❌ ❌ 5
Learning 3D Dense Correspondence via Canonical Point Autoencoder ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning Causal Semantic Representation for Out-of-Distribution Prediction ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning Collaborative Policies to Solve NP-hard Routing Problems ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM) ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning Conjoint Attentions for Graph Neural Nets ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Learning Debiased Representation via Disentangled Feature Augmentation ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning Debiased and Disentangled Representations for Semantic Segmentation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning Disentangled Behavior Embeddings ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Learning Distilled Collaboration Graph for Multi-Agent Perception ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning Diverse Policies in MOBA Games via Macro-Goals ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Learning Domain Invariant Representations in Goal-conditioned Block MDPs ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning Equilibria in Matching Markets from Bandit Feedback ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning Fast-Inference Bayesian Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning Frequency Domain Approximation for Binary Neural Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning Generalized Gumbel-max Causal Mechanisms ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning Graph Cellular Automata ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning Graph Models for Retrosynthesis Prediction ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Learning Hard Optimization Problems: A Data Generation Perspective ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning Knowledge Graph-based World Models of Textual Environments ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning Large Neighborhood Search Policy for Integer Programming ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
Learning Markov State Abstractions for Deep Reinforcement Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning Models for Actionable Recourse ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning Nonparametric Volterra Kernels with Gaussian Processes ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning One Representation to Optimize All Rewards ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Learning Optimal Predictive Checklists ✅ ✅ ✅ ✅ ✅ ✅ ❌ 6
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Learning Riemannian metric for disease progression modeling ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning Robust Hierarchical Patterns of Human Brain across Many fMRI Studies ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning Semantic Representations to Verify Hardware Designs ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning Signal-Agnostic Manifolds of Neural Fields ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning Space Partitions for Path Planning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Learning State Representations from Random Deep Action-conditional Predictions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning Student-Friendly Teacher Networks for Knowledge Distillation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Learning Transferable Adversarial Perturbations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning Transferable Features for Point Cloud Detection via 3D Contrastive Co-training ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning Treatment Effects in Panels with General Intervention Patterns ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Learning a Single Neuron with Bias Using Gradient Descent ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Learning and Generalization in RNNs ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Learning curves of generic features maps for realistic datasets with a teacher-student model ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Learning in Multi-Stage Decentralized Matching Markets ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning in Non-Cooperative Configurable Markov Decision Processes ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Learning in two-player zero-sum partially observable Markov games with perfect recall ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Learning interaction rules from multi-animal trajectories via augmented behavioral models ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
Learning latent causal graphs via mixture oracles ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Learning rule influences recurrent network representations but not attractor structure in decision-making tasks ❌ ❌ ❌ ✅ ✅ ❌ ✅ 3
Learning the optimal Tikhonov regularizer for inverse problems ❌ ✅ ❌ ❌ ✅ ✅ ✅ 4
Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Learning to Assimilate in Chaotic Dynamical Systems ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
Learning to Combine Per-Example Solutions for Neural Program Synthesis ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Learning to Compose Visual Relations ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Learning to Draw: Emergent Communication through Sketching ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning to Elect ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning to Generate Visual Questions with Noisy Supervision ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning to Ground Multi-Agent Communication with Autoencoders ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning to Learn Dense Gaussian Processes for Few-Shot Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning to Learn Graph Topologies ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Learning to Predict Trustworthiness with Steep Slope Loss ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning to Schedule Heuristics in Branch and Bound ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Learning to See by Looking at Noise ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Learning to Select Exogenous Events for Marked Temporal Point Process ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization ✅ ✅ ❌ ❌ ✅ ❌ ❌ 3
Learning to Synthesize Programs as Interpretable and Generalizable Policies ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning to dehaze with polarization ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Learning to delegate for large-scale vehicle routing ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning where to learn: Gradient sparsity in meta and continual learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning with Algorithmic Supervision via Continuous Relaxations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning with Holographic Reduced Representations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning with Labeling Induced Abstentions ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning with Noisy Correspondence for Cross-modal Matching ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning with User-Level Privacy ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Learning-to-learn non-convex piecewise-Lipschitz functions ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Least Square Calibration for Peer Reviews ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Leveraging Distribution Alignment via Stein Path for Cross-Domain Cold-Start Recommendation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Leveraging SE(3) Equivariance for Self-supervised Category-Level Object Pose Estimation from Point Clouds ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
Lifelong Domain Adaptation via Consolidated Internal Distribution ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field training ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Linear Convergence of Gradient Methods for Estimating Structured Transition Matrices in High-dimensional Vector Autoregressive Models ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Linear and Kernel Classification in the Streaming Model: Improved Bounds for Heavy Hitters ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Linear-Time Probabilistic Solution of Boundary Value Problems ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Lip to Speech Synthesis with Visual Context Attentional GAN ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
List-Decodable Mean Estimation in Nearly-PCA Time ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Littlestone Classes are Privately Online Learnable ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Local Differential Privacy for Regret Minimization in Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Local Explanation of Dialogue Response Generation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Local Hyper-Flow Diffusion ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Local plasticity rules can learn deep representations using self-supervised contrastive predictions ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Local policy search with Bayesian optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Locality Sensitive Teaching ✅ ❌ ✅ ✅ ✅ ✅ ❌ 5
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Localization with Sampling-Argmax ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Localization, Convexity, and Star Aggregation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models ✅ ✅ ✅ ✅ ✅ ❌ ❌ 5
Locally differentially private estimation of functionals of discrete distributions ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Locally private online change point detection ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Logarithmic Regret from Sublinear Hints ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Logarithmic Regret in Feature-based Dynamic Pricing ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Long Short-Term Transformer for Online Action Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Long-Short Transformer: Efficient Transformers for Language and Vision ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Loss function based second-order Jensen inequality and its application to particle variational inference ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Lossy Compression for Lossless Prediction ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Low-Fidelity Video Encoder Optimization for Temporal Action Localization ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Low-Rank Constraints for Fast Inference in Structured Models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Low-Rank Subspaces in GANs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Low-dimensional Structure in the Space of Language Representations is Reflected in Brain Responses ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Luna: Linear Unified Nested Attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
MADE: Exploration via Maximizing Deviation from Explored Regions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
MAU: A Motion-Aware Unit for Video Prediction and Beyond ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
MCMC Variational Inference via Uncorrected Hamiltonian Annealing ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
MERLOT: Multimodal Neural Script Knowledge Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
MICo: Improved representations via sampling-based state similarity for Markov decision processes ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
MLP-Mixer: An all-MLP Architecture for Vision ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
MOMA: Multi-Object Multi-Actor Activity Parsing ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
MST: Masked Self-Supervised Transformer for Visual Representation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Machine Learning for Variance Reduction in Online Experiments ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Machine learning structure preserving brackets for forecasting irreversible processes ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
Machine versus Human Attention in Deep Reinforcement Learning Tasks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
MagNet: A Neural Network for Directed Graphs ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Making a (Counterfactual) Difference One Rationale at a Time ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Making the most of your day: online learning for optimal allocation of time ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Manifold Topology Divergence: a Framework for Comparing Data Manifolds. ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Manipulating SGD with Data Ordering Attacks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Margin-Independent Online Multiclass Learning via Convex Geometry ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Marginalised Gaussian Processes with Nested Sampling ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
MarioNette: Self-Supervised Sprite Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Mastering Atari Games with Limited Data ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Matching a Desired Causal State via Shift Interventions ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Matrix encoding networks for neural combinatorial optimization ❌ ✅ ❌ ❌ ✅ ✅ ✅ 4
Matrix factorisation and the interpretation of geodesic distance ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Maximum Likelihood Training of Score-Based Diffusion Models ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Mean-based Best Arm Identification in Stochastic Bandits under Reward Contamination ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Measuring Generalization with Optimal Transport ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Medical Dead-ends and Learning to Identify High-Risk States and Treatments ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Memory Efficient Meta-Learning with Large Images ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Memory-Efficient Approximation Algorithms for Max-k-Cut and Correlation Clustering ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Memory-efficient Patch-based Inference for Tiny Deep Learning ❌ ❌ ✅ ✅ ✅ ❌ ❌ 3
Meta Internal Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Meta Learning Backpropagation And Improving It ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Meta-Adaptive Nonlinear Control: Theory and Algorithms ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Meta-Learning Reliable Priors in the Function Space ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Meta-Learning Sparse Implicit Neural Representations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Meta-Learning for Relative Density-Ratio Estimation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Meta-learning to Improve Pre-training ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Meta-learning with an Adaptive Task Scheduler ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Metropolis-Hastings Data Augmentation for Graph Neural Networks ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
Mind the Gap: Assessing Temporal Generalization in Neural Language Models ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Minimax Regret for Stochastic Shortest Path ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Minimizing Polarization and Disagreement in Social Networks via Link Recommendation ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Mining the Benefits of Two-stage and One-stage HOI Detection ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Mirror Langevin Monte Carlo: the Case Under Isoperimetry ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Misspecified Gaussian Process Bandit Optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Mitigating Forgetting in Online Continual Learning with Neuron Calibration ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Mixability made efficient: Fast online multiclass logistic regression ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Mixed Supervised Object Detection by Transferring Mask Prior and Semantic Similarity ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Mixture Proportion Estimation and PU Learning:A Modern Approach ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Mixture weights optimisation for Alpha-Divergence Variational Inference ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
MobILE: Model-Based Imitation Learning From Observation Alone ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Modality-Agnostic Topology Aware Localization ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Model Selection for Bayesian Autoencoders ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Model-Based Domain Generalization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Model-Based Episodic Memory Induces Dynamic Hybrid Controls ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Model-Based Reinforcement Learning via Imagination with Derived Memory ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Modified Frank Wolfe in Probability Space ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
Modular Gaussian Processes for Transfer Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Momentum Centering and Asynchronous Update for Adaptive Gradient Methods ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Monte Carlo Tree Search With Iteratively Refining State Abstractions ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Morié Attack (MA): A New Potential Risk of Screen Photos ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Moser Flow: Divergence-based Generative Modeling on Manifolds ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Multi-Agent Reinforcement Learning in Stochastic Networked Systems ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Multi-Facet Clustering Variational Autoencoders ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Multi-Label Learning with Pairwise Relevance Ordering ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Multi-Objective Meta Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Multi-Person 3D Motion Prediction with Multi-Range Transformers ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Multi-Scale Representation Learning on Proteins ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Multi-View Representation Learning via Total Correlation Objective ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Multi-armed Bandit Requiring Monotone Arm Sequences ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Multi-modal Dependency Tree for Video Captioning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Multi-task Learning of Order-Consistent Causal Graphs ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Multi-view Contrastive Graph Clustering ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Multiclass Boosting and the Cost of Weak Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Multiclass versus Binary Differentially Private PAC Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Multilingual Pre-training with Universal Dependency Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Multimodal Few-Shot Learning with Frozen Language Models ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Multimodal Virtual Point 3D Detection ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Multimodal and Multilingual Embeddings for Large-Scale Speech Mining ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Multiple Descent: Design Your Own Generalization Curve ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Multiwavelet-based Operator Learning for Differential Equations ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
NAS-Bench-x11 and the Power of Learning Curves ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
NN-Baker: A Neural-network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
NORESQA: A Framework for Speech Quality Assessment using Non-Matching References ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
NTopo: Mesh-free Topology Optimization using Implicit Neural Representations ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Natural continual learning: success is a journey, not (just) a destination ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Navigating to the Best Policy in Markov Decision Processes ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
NeRV: Neural Representations for Videos ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Near Optimal Policy Optimization via REPS ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Near-Optimal No-Regret Learning in General Games ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Nearly Horizon-Free Offline Reinforcement Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Nearly-Tight and Oblivious Algorithms for Explainable Clustering ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Neighborhood Reconstructing Autoencoders ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Nested Counterfactual Identification from Arbitrary Surrogate Experiments ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Nested Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Nested Variational Inference ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Network-to-Network Regularization: Enforcing Occam's Razor to Improve Generalization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Neural Active Learning with Performance Guarantees ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Neural Additive Models: Interpretable Machine Learning with Neural Nets ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Algorithmic Reasoners are Implicit Planners ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Neural Architecture Dilation for Adversarial Robustness ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Neural Auto-Curricula in Two-Player Zero-Sum Games ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Bootstrapper ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Neural Circuit Synthesis from Specification Patterns ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Distance Embeddings for Biological Sequences ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Dubber: Dubbing for Videos According to Scripts ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Neural Flows: Efficient Alternative to Neural ODEs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions ❌ ✅ ❌ ✅ ❌ ❌ ❌ 2
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Neural Production Systems ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Program Generation Modulo Static Analysis ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Pseudo-Label Optimism for the Bank Loan Problem ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Relightable Participating Media Rendering ❌ ❌ ❌ ✅ ✅ ❌ ✅ 3
Neural Routing by Memory ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Scene Flow Prior ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Neural Tangent Kernel Maximum Mean Discrepancy ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Neural Trees for Learning on Graphs ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural optimal feedback control with local learning rules ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
NeuroMLR: Robust & Reliable Route Recommendation on Road Networks ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Never Go Full Batch (in Stochastic Convex Optimization) ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
No RL, No Simulation: Learning to Navigate without Navigating ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
No Regrets for Learning the Prior in Bandits ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
No-Press Diplomacy from Scratch ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
No-regret Online Learning over Riemannian Manifolds ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Node Dependent Local Smoothing for Scalable Graph Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Noether Networks: meta-learning useful conserved quantities ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Noether’s Learning Dynamics: Role of Symmetry Breaking in Neural Networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Noise2Score: Tweedie’s Approach to Self-Supervised Image Denoising without Clean Images ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Noisy Recurrent Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Non-Gaussian Gaussian Processes for Few-Shot Regression ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Non-asymptotic Error Bounds for Bidirectional GANs ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Non-local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Nonparametric estimation of continuous DPPs with kernel methods ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data ✅ ❌ ❌ ✅ ✅ ❌ ✅ 4
Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Not All Low-Pass Filters are Robust in Graph Convolutional Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Novel Upper Bounds for the Constrained Most Probable Explanation Task ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
NovelD: A Simple yet Effective Exploration Criterion ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Numerical Composition of Differential Privacy ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Numerical influence of ReLU’(0) on backpropagation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
Object DGCNN: 3D Object Detection using Dynamic Graphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Object-Centric Representation Learning with Generative Spatial-Temporal Factorization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Object-aware Contrastive Learning for Debiased Scene Representation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Observation-Free Attacks on Stochastic Bandits ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
OctField: Hierarchical Implicit Functions for 3D Modeling ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Off-Policy Risk Assessment in Contextual Bandits ✅ ❌ ✅ ❌ ❌ ✅ ✅ 4
Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Offline Model-based Adaptable Policy Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Offline RL Without Off-Policy Evaluation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Offline Reinforcement Learning as One Big Sequence Modeling Problem ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Offline Reinforcement Learning with Reverse Model-based Imagination ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
On Calibration and Out-of-Domain Generalization ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
On Component Interactions in Two-Stage Recommender Systems ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
On Contrastive Representations of Stochastic Processes ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On Effective Scheduling of Model-based Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
On Empirical Risk Minimization with Dependent and Heavy-Tailed Data ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On Episodes, Prototypical Networks, and Few-Shot Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On Inductive Biases for Heterogeneous Treatment Effect Estimation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On Joint Learning for Solving Placement and Routing in Chip Design ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
On Large-Cohort Training for Federated Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On Linear Stability of SGD and Input-Smoothness of Neural Networks ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
On Locality of Local Explanation Models ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
On Margin-Based Cluster Recovery with Oracle Queries ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On Memorization in Probabilistic Deep Generative Models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On Optimal Interpolation in Linear Regression ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
On Optimal Robustness to Adversarial Corruption in Online Decision Problems ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On Provable Benefits of Depth in Training Graph Convolutional Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
On Robust Optimal Transport: Computational Complexity and Barycenter Computation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
On Success and Simplicity: A Second Look at Transferable Targeted Attacks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On Training Implicit Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On UMAP's True Loss Function ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On learning sparse vectors from mixture of responses ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On sensitivity of meta-learning to support data ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
On the Algorithmic Stability of Adversarial Training ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
On the Bias-Variance-Cost Tradeoff of Stochastic Optimization ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
On the Convergence of Step Decay Step-Size for Stochastic Optimization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
On the Cryptographic Hardness of Learning Single Periodic Neurons ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On the Equivalence between Neural Network and Support Vector Machine ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On the Estimation Bias in Double Q-Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Existence of The Adversarial Bayes Classifier ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the Expected Complexity of Maxout Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
On the Expressivity of Markov Reward ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On the Frequency Bias of Generative Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Generative Utility of Cyclic Conditionals ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Importance of Gradients for Detecting Distributional Shifts in the Wild ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Out-of-distribution Generalization of Probabilistic Image Modelling ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Power of Differentiable Learning versus PAC and SQ Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On the Power of Edge Independent Graph Models ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On the Provable Generalization of Recurrent Neural Networks ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On the Rate of Convergence of Regularized Learning in Games: From Bandits and Uncertainty to Optimism and Beyond ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
On the Representation Power of Set Pooling Networks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
On the Representation of Solutions to Elliptic PDEs in Barron Spaces ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the Role of Optimization in Double Descent: A Least Squares Study ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On the Sample Complexity of Learning under Geometric Stability ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
On the Sample Complexity of Privately Learning Axis-Aligned Rectangles ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On the Second-order Convergence Properties of Random Search Methods ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
On the Stochastic Stability of Deep Markov Models ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the Suboptimality of Thompson Sampling in High Dimensions ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
On the Theory of Reinforcement Learning with Once-per-Episode Feedback ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
On the Universality of Graph Neural Networks on Large Random Graphs ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs) ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the Value of Infinite Gradients in Variational Autoencoder Models ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
On the Value of Interaction and Function Approximation in Imitation Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
On the Variance of the Fisher Information for Deep Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the interplay between data structure and loss function in classification problems ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
One Explanation is Not Enough: Structured Attention Graphs for Image Classification ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
One More Step Towards Reality: Cooperative Bandits with Imperfect Communication ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Online Active Learning with Surrogate Loss Functions ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Online Adaptation to Label Distribution Shift ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Online Control of Unknown Time-Varying Dynamical Systems ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Online Convex Optimization with Continuous Switching Constraint ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Online Facility Location with Multiple Advice ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Online Knapsack with Frequency Predictions ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Online Learning Of Neural Computations From Sparse Temporal Feedback ❌ ✅ ❌ ❌ ✅ ✅ ✅ 4
Online Learning and Control of Complex Dynamical Systems from Sensory Input ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Online Learning in Periodic Zero-Sum Games ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Online Market Equilibrium with Application to Fair Division ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Online Meta-Learning via Learning with Layer-Distributed Memory ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Online Multi-Armed Bandits with Adaptive Inference ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Online Robust Reinforcement Learning with Model Uncertainty ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Online Selective Classification with Limited Feedback ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
Online Variational Filtering and Parameter Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Online and Offline Reinforcement Learning by Planning with a Learned Model ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
Online false discovery rate control for anomaly detection in time series ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Online learning in MDPs with linear function approximation and bandit feedback. ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Only Train Once: A One-Shot Neural Network Training And Pruning Framework ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Open Rule Induction ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Optimal Algorithms for Stochastic Contextual Preference Bandits ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Optimal Best-Arm Identification Methods for Tail-Risk Measures ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Optimal Order Simple Regret for Gaussian Process Bandits ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Optimal Policies Tend To Seek Power ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Optimal Rates for Nonparametric Density Estimation under Communication Constraints ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Optimal Rates for Random Order Online Optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Optimal Sketching for Trace Estimation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Optimal Underdamped Langevin MCMC Method ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Optimal prediction of Markov chains with and without spectral gap ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Optimality and Stability in Federated Learning: A Game-theoretic Approach ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Optimality of variational inference for stochasticblock model with missing links ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Optimizing Conditional Value-At-Risk of Black-Box Functions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Optimizing Reusable Knowledge for Continual Learning via Metalearning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Oracle Complexity in Nonsmooth Nonconvex Optimization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Out-of-Distribution Generalization in Kernel Regression ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Outcome-Driven Reinforcement Learning via Variational Inference ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Overcoming the Convex Barrier for Simplex Inputs ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Overinterpretation reveals image classification model pathologies ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Overlapping Spaces for Compact Graph Representations ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Overparameterization Improves Robustness to Covariate Shift in High Dimensions ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
PCA Initialization for Approximate Message Passing in Rotationally Invariant Models ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
PLUGIn: A simple algorithm for inverting generative models with recovery guarantees ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
PSD Representations for Effective Probability Models ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Panoptic 3D Scene Reconstruction From a Single RGB Image ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Parallel and Efficient Hierarchical k-Median Clustering ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Parallelizing Thompson Sampling ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Parameter Inference with Bifurcation Diagrams ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Parameter Prediction for Unseen Deep Architectures ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Parameter-free HE-friendly Logistic Regression ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Parameterized Knowledge Transfer for Personalized Federated Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Parametric Complexity Bounds for Approximating PDEs with Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Parametrized Quantum Policies for Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Pareto Domain Adaptation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Pareto-Optimal Learning-Augmented Algorithms for Online Conversion Problems ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Partial success in closing the gap between human and machine vision ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Particle Cloud Generation with Message Passing Generative Adversarial Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Particle Dual Averaging: Optimization of Mean Field Neural Network with Global Convergence Rate Analysis ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Partition and Code: learning how to compress graphs ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Partition-Based Formulations for Mixed-Integer Optimization of Trained ReLU Neural Networks ❌ ✅ ✅ ❌ ❌ ✅ ✅ 4
Passive attention in artificial neural networks predicts human visual selectivity ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
PatchGame: Learning to Signal Mid-level Patches in Referential Games ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Pay Attention to MLPs ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Per-Pixel Classification is Not All You Need for Semantic Segmentation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Perceptual Score: What Data Modalities Does Your Model Perceive? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Periodic Activation Functions Induce Stationarity ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Permuton-induced Chinese Restaurant Process ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Personalized Federated Learning With Gaussian Processes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Perturb-and-max-product: Sampling and learning in discrete energy-based models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Perturbation Theory for the Information Bottleneck ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
PettingZoo: Gym for Multi-Agent Reinforcement Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Photonic Differential Privacy with Direct Feedback Alignment ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
PiRank: Scalable Learning To Rank via Differentiable Sorting ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Pipeline Combinators for Gradual AutoML ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Piper: Multidimensional Planner for DNN Parallelization ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Planning from Pixels in Environments with Combinatorially Hard Search Spaces ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Play to Grade: Testing Coding Games as Classifying Markov Decision Process ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Pointwise Bounds for Distribution Estimation under Communication Constraints ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
PolarStream: Streaming Object Detection and Segmentation with Polar Pillars ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Policy Learning Using Weak Supervision ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Pooling by Sliced-Wasserstein Embedding ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
PortaSpeech: Portable and High-Quality Generative Text-to-Speech ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Post-Contextual-Bandit Inference ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Post-Training Quantization for Vision Transformer ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Post-Training Sparsity-Aware Quantization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Post-processing for Individual Fairness ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Posterior Collapse and Latent Variable Non-identifiability ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Posterior Meta-Replay for Continual Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Powerpropagation: A sparsity inducing weight reparameterisation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Practical Near Neighbor Search via Group Testing ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Pragmatic Image Compression for Human-in-the-Loop Decision-Making ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Precise characterization of the prior predictive distribution of deep ReLU networks ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Predicting Deep Neural Network Generalization with Perturbation Response Curves ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Predicting Event Memorability from Contextual Visual Semantics ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
Predicting Molecular Conformation via Dynamic Graph Score Matching ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Predicting What You Already Know Helps: Provable Self-Supervised Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Preserved central model for faster bidirectional compression in distributed settings ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Pretraining Representations for Data-Efficient Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Prior-independent Dynamic Auctions for a Value-maximizing Buyer ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Private Non-smooth ERM and SCO in Subquadratic Steps ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Private and Non-private Uniformity Testing for Ranking Data ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Private learning implies quantum stability ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Privately Learning Mixtures of Axis-Aligned Gaussians ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Privately Learning Subspaces ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Privately Publishable Per-instance Privacy ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
ProTo: Program-Guided Transformer for Program-Guided Tasks ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Probabilistic Attention for Interactive Segmentation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Probabilistic Forecasting: A Level-Set Approach ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Probabilistic Margins for Instance Reweighting in Adversarial Training ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Probabilistic Tensor Decomposition of Neural Population Spiking Activity ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Probabilistic Transformer For Time Series Analysis ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Probability Paths and the Structure of Predictions over Time ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-and-Language Pre-training ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Program Synthesis Guided Reinforcement Learning for Partially Observed Environments ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Progressive Coordinate Transforms for Monocular 3D Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Progressive Feature Interaction Search for Deep Sparse Network ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Projected GANs Converge Faster ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Proper Value Equivalence ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Property-Aware Relation Networks for Few-Shot Molecular Property Prediction ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Proportional Participatory Budgeting with Additive Utilities ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Provable Representation Learning for Imitation with Contrastive Fourier Features ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Provably Faster Algorithms for Bilevel Optimization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Provably Strict Generalisation Benefit for Invariance in Kernel Methods ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Provably efficient multi-task reinforcement learning with model transfer ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Provably efficient, succinct, and precise explanations ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Pruning Randomly Initialized Neural Networks with Iterative Randomization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Pseudo-Spherical Contrastive Divergence ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Pure Exploration in Kernel and Neural Bandits ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Quantifying and Improving Transferability in Domain Generalization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
R-Drop: Regularized Dropout for Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
RIM: Reliable Influence-based Active Learning on Graphs ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
RL for Latent MDPs: Regret Guarantees and a Lower Bound ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
RMM: Reinforced Memory Management for Class-Incremental Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
ROI Maximization in Stochastic Online Decision-Making ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Random Noise Defense Against Query-Based Black-Box Attacks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Random Shuffling Beats SGD Only After Many Epochs on Ill-Conditioned Problems ❌ ✅ ❌ ❌ ✅ ✅ ✅ 4
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Ranking Policy Decisions ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Rate-Optimal Subspace Estimation on Random Graphs ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Re-ranking for image retrieval and transductive few-shot classification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
ReAct: Out-of-distribution Detection With Rectified Activations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
ReLU Regression with Massart Noise ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
ReSSL: Relational Self-Supervised Learning with Weak Augmentation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Realistic evaluation of transductive few-shot learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Rebounding Bandits for Modeling Satiation Effects ✅ ❌ ❌ ❌ ❌ ✅ ✅ 3
Recognizing Vector Graphics without Rasterization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Reconstruction for Powerful Graph Representations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Recovering Latent Causal Factor for Generalization to Distributional Shifts ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Rectangular Flows for Manifold Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Rectifying the Shortcut Learning of Background for Few-Shot Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Redesigning the Transformer Architecture with Insights from Multi-particle Dynamical Systems ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Referring Transformer: A One-step Approach to Multi-task Visual Grounding ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Refined Learning Bounds for Kernel and Approximate $k$-Means ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
Refining Language Models with Compositional Explanations ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Reformulating Zero-shot Action Recognition for Multi-label Actions ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Regime Switching Bandits ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Regret Bounds for Gaussian-Process Optimization in Large Domains ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Regret Minimization Experience Replay in Off-Policy Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Regularization in ResNet with Stochastic Depth ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Regularized Softmax Deep Multi-Agent Q-Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Regulating algorithmic filtering on social media ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Reinforcement Learning Enhanced Explainer for Graph Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Reinforcement Learning based Disease Progression Model for Alzheimer’s Disease ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Reinforcement Learning in Newcomblike Environments ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Reinforcement Learning in Reward-Mixing MDPs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Reinforcement Learning with Latent Flow ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision Processes ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Reinforcement learning for optimization of variational quantum circuit architectures ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Relational Self-Attention: What's Missing in Attention for Video Understanding ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Relative Flatness and Generalization ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Relative Uncertainty Learning for Facial Expression Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Relative stability toward diffeomorphisms indicates performance in deep nets ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Relaxed Marginal Consistency for Differentially Private Query Answering ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Relaxing Local Robustness ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
RelaySum for Decentralized Deep Learning on Heterogeneous Data ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Reliable Decisions with Threshold Calibration ✅ ✅ ✅ ✅ ✅ ❌ ❌ 5
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Remember What You Want to Forget: Algorithms for Machine Unlearning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Replay-Guided Adversarial Environment Design ✅ ✅ ❌ ✅ ✅ ✅ ✅ 6
Representation Costs of Linear Neural Networks: Analysis and Design ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Representation Learning Beyond Linear Prediction Functions ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Representation Learning for Event-based Visuomotor Policies ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Representation Learning on Spatial Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Representing Hyperbolic Space Accurately using Multi-Component Floats ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Representing Long-Range Context for Graph Neural Networks with Global Attention ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Repulsive Deep Ensembles are Bayesian ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
ResT: An Efficient Transformer for Visual Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Residual Pathway Priors for Soft Equivariance Constraints ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Residual Relaxation for Multi-view Representation Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Residual2Vec: Debiasing graph embedding with random graphs ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Rethinking Graph Transformers with Spectral Attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Rethinking Neural Operations for Diverse Tasks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Rethinking gradient sparsification as total error minimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Rethinking the Pruning Criteria for Convolutional Neural Network ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Rethinking the Variational Interpretation of Accelerated Optimization Methods ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Retiring Adult: New Datasets for Fair Machine Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Revealing and Protecting Labels in Distributed Training ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Revenue maximization via machine learning with noisy data ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Reverse engineering learned optimizers reveals known and novel mechanisms ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Reverse-Complement Equivariant Networks for DNA Sequences ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Revisiting 3D Object Detection From an Egocentric Perspective ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Revisiting Deep Learning Models for Tabular Data ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Revisiting Model Stitching to Compare Neural Representations ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Revisiting ResNets: Improved Training and Scaling Strategies ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Revisiting Smoothed Online Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Revisiting the Calibration of Modern Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Reward is enough for convex MDPs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Reward-Free Model-Based Reinforcement Learning with Linear Function Approximation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Risk Monotonicity in Statistical Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Risk-Averse Bayes-Adaptive Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Risk-Aware Transfer in Reinforcement Learning using Successor Features ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Risk-averse Heteroscedastic Bayesian Optimization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
RoMA: Robust Model Adaptation for Offline Model-based Optimization ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Robust Allocations with Diversity Constraints ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Robust Auction Design in the Auto-bidding World ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Robust Compressed Sensing MRI with Deep Generative Priors ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Robust Contrastive Learning Using Negative Samples with Diminished Semantics ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Robust Counterfactual Explanations on Graph Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Robust Deep Reinforcement Learning through Adversarial Loss ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Robust Generalization despite Distribution Shift via Minimum Discriminating Information ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Robust Implicit Networks via Non-Euclidean Contractions ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Robust Learning of Optimal Auctions ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Robust Online Correlation Clustering ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Robust Optimization for Multilingual Translation with Imbalanced Data ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Robust Pose Estimation in Crowded Scenes with Direct Pose-Level Inference ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Robust Predictable Control ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
Robust Regression Revisited: Acceleration and Improved Estimation Rates ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Robust Visual Reasoning via Language Guided Neural Module Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Robust and Decomposable Average Precision for Image Retrieval ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems ❌ ❌ ✅ ❌ ✅ ❌ ❌ 2
Robust and differentially private mean estimation ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Robustifying Algorithms of Learning Latent Trees with Vector Variables ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Robustness between the worst and average case ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Robustness of Graph Neural Networks at Scale ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Robustness via Uncertainty-aware Cycle Consistency ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Roto-translated Local Coordinate Frames For Interacting Dynamical Systems ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Row-clustering of a Point Process-valued Matrix ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
S$^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
SBO-RNN: Reformulating Recurrent Neural Networks via Stochastic Bilevel Optimization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
SILG: The Multi-domain Symbolic Interactive Language Grounding Benchmark ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression ❌ ✅ ✅ ❌ ❌ ✅ ✅ 4
SNIPS: Solving Noisy Inverse Problems Stochastically ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
SOFT: Softmax-free Transformer with Linear Complexity ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
SOLQ: Segmenting Objects by Learning Queries ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
SOPE: Spectrum of Off-Policy Estimators ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
SQALER: Scaling Question Answering by Decoupling Multi-Hop and Logical Reasoning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
SSMF: Shifting Seasonal Matrix Factorization ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
SWAD: Domain Generalization by Seeking Flat Minima ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Safe Policy Optimization with Local Generalized Linear Function Approximations ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Safe Pontryagin Differentiable Programming ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Safe Reinforcement Learning by Imagining the Near Future ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Safe Reinforcement Learning with Natural Language Constraints ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Sageflow: Robust Federated Learning against Both Stragglers and Adversaries ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Sample Selection for Fair and Robust Training ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Sampling with Trusthworthy Constraints: A Variational Gradient Framework ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Scalable Diverse Model Selection for Accessible Transfer Learning ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
Scalable Inference in SDEs by Direct Matching of the Fokker–Planck–Kolmogorov Equation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Scalable Inference of Sparsely-changing Gaussian Markov Random Fields ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Scalable Intervention Target Estimation in Linear Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Scalable Neural Data Server: A Data Recommender for Transfer Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Scalable Online Planning via Reinforcement Learning Fine-Tuning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Scalable Rule-Based Representation Learning for Interpretable Classification ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Scalable Thompson Sampling using Sparse Gaussian Process Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Scalable and Stable Surrogates for Flexible Classifiers with Fairness Constraints ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Scalars are universal: Equivariant machine learning, structured like classical physics ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Scaling Gaussian Processes with Derivative Information Using Variational Inference ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Scaling Neural Tangent Kernels via Sketching and Random Features ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Scaling Up Exact Neural Network Compression by ReLU Stability ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Scaling Vision with Sparse Mixture of Experts ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Scatterbrain: Unifying Sparse and Low-rank Attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Scheduling jobs with stochastic holding costs ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Score-based Generative Modeling in Latent Space ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Score-based Generative Neural Networks for Large-Scale Optimal Transport ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Searching Parameterized AP Loss for Object Detection ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Searching for Efficient Transformers for Language Modeling ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Searching the Search Space of Vision Transformer ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Second-Order Neural ODE Optimizer ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
See More for Scene: Pairwise Consistency Learning for Scene Classification ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Selective Sampling for Online Best-arm Identification ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Self-Adaptable Point Processes with Nonparametric Time Decays ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Self-Consistent Models and Values ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Self-Instantiated Recurrent Units with Dynamic Soft Recursion ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Self-Interpretable Model with Transformation Equivariant Interpretation ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Self-Supervised Bug Detection and Repair ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Self-Supervised GANs with Label Augmentation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Self-Supervised Learning Disentangled Group Representation as Feature ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Self-Supervised Learning with Kernel Dependence Maximization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Self-Supervised Multi-Object Tracking with Cross-input Consistency ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Sequence-to-Sequence Learning with Latent Neural Grammars ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Sequential Algorithms for Testing Closeness of Distributions ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Sequential Causal Imitation Learning with Unobserved Confounders ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Set Prediction in the Latent Space ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Settling the Variance of Multi-Agent Policy Gradients ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Shape As Points: A Differentiable Poisson Solver ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Shape Registration in the Time of Transformers ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Shapeshifter: a Parameter-efficient Transformer using Factorized Reshaped Matrices ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Shaping embodied agent behavior with activity-context priors from egocentric video ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Shapley Residuals: Quantifying the limits of the Shapley value for explanations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Shared Independent Component Analysis for Multi-Subject Neuroimaging ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Sharp Impossibility Results for Hyper-graph Testing ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Shift Invariance Can Reduce Adversarial Robustness ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Shifted Chunk Transformer for Spatio-Temporal Representational Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Sifting through the noise: Universal first-order methods for stochastic variational inequalities ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Sim and Real: Better Together ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Similarity and Matching of Neural Network Representations ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
SketchGen: Generating Constrained CAD Sketches ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Skipping the Frame-Level: Event-Based Piano Transcription With Neural Semi-CRFs ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Slice Sampling Reparameterization Gradients ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Sliced Mutual Information: A Scalable Measure of Statistical Dependence ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Smooth Bilevel Programming for Sparse Regularization ❌ ✅ ✅ ✅ ✅ ❌ ❌ 4
Smooth Normalizing Flows ❌ ❌ ❌ ❌ ❌ ✅ ✅ 2
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Soft Calibration Objectives for Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Solving Graph-based Public Goods Games with Tree Search and Imitation Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Solving Soft Clustering Ensemble via $k$-Sparse Discrete Wasserstein Barycenter ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Space-time Mixing Attention for Video Transformer ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Sparse Flows: Pruning Continuous-depth Models ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Sparse Spiking Gradient Descent ❌ ❌ ✅ ❌ ✅ ❌ ❌ 2
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Sparse Uncertainty Representation in Deep Learning with Inducing Weights ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Sparse is Enough in Scaling Transformers ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Spatio-Temporal Variational Gaussian Processes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Spectral embedding for dynamic networks with stability guarantees ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Speech-T: Transducer for Text to Speech and Beyond ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Speedy Performance Estimation for Neural Architecture Search ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Spherical Motion Dynamics: Learning Dynamics of Normalized Neural Network using SGD and Weight Decay ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Spot the Difference: Detection of Topological Changes via Geometric Alignment ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Stabilizing Dynamical Systems via Policy Gradient Methods ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Stateful ODE-Nets using Basis Function Expansions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Stateful Strategic Regression ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Statistical Inference with M-Estimators on Adaptively Collected Data ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Statistical Query Lower Bounds for List-Decodable Linear Regression ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Statistical Undecidability in Linear, Non-Gaussian Causal Models in the Presence of Latent Confounders ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Statistically and Computationally Efficient Linear Meta-representation Learning ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
Stochastic $L^\natural$-convex Function Minimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Stochastic Bias-Reduced Gradient Methods ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Stochastic Multi-Armed Bandits with Control Variates ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Stochastic bandits with groups of similar arms. ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Storchastic: A Framework for General Stochastic Automatic Differentiation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Strategic Behavior is Bliss: Iterative Voting Improves Social Welfare ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Streaming Belief Propagation for Community Detection ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Streaming Linear System Identification with Reverse Experience Replay ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Stronger NAS with Weaker Predictors ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Structural Credit Assignment in Neural Networks using Reinforcement Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Structure-Aware Random Fourier Kernel for Graphs ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Structured Denoising Diffusion Models in Discrete State-Spaces ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Structured Dropout Variational Inference for Bayesian Neural Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Structured Reordering for Modeling Latent Alignments in Sequence Transduction ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Structured in Space, Randomized in Time: Leveraging Dropout in RNNs for Efficient Training ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Stylized Dialogue Generation with Multi-Pass Dual Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Sub-Linear Memory: How to Make Performers SLiM ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Subgame solving without common knowledge ✅ ❌ ❌ ❌ ✅ ✅ ✅ 4
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Subgoal Search For Complex Reasoning Tasks ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Subgraph Federated Learning with Missing Neighbor Generation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Subgroup Generalization and Fairness of Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Submodular + Concave ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Subquadratic Overparameterization for Shallow Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Supervising the Transfer of Reasoning Patterns in VQA ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Support Recovery of Sparse Signals from a Mixture of Linear Measurements ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Support vector machines and linear regression coincide with very high-dimensional features ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Surrogate Regret Bounds for Polyhedral Losses ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
Systematic Generalization with Edge Transformers ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
TAAC: Temporally Abstract Actor-Critic for Continuous Control ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Tactical Optimism and Pessimism for Deep Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Targeted Neural Dynamical Modeling ❌ ✅ ✅ ❌ ❌ ✅ ✅ 4
Task-Adaptive Neural Network Search with Meta-Contrastive Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Taxonomizing local versus global structure in neural network loss landscapes ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Teachable Reinforcement Learning via Advice Distillation ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Teaching an Active Learner with Contrastive Examples ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Techniques for Symbol Grounding with SATNet ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Temporal-attentive Covariance Pooling Networks for Video Recognition ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Temporally Abstract Partial Models ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Tensor Normal Training for Deep Learning Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Tensor decompositions of higher-order correlations by nonlinear Hebbian plasticity ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs ❌ ❌ ✅ ❌ ✅ ✅ ❌ 3
Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Test-Time Personalization with a Transformer for Human Pose Estimation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Test-time Collective Prediction ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Testing Probabilistic Circuits ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
The Adaptive Doubly Robust Estimator and a Paradox Concerning Logging Policy ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
The Benefits of Implicit Regularization from SGD in Least Squares Problems ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The Causal-Neural Connection: Expressiveness, Learnability, and Inference ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
The Complexity of Bayesian Network Learning: Revisiting the Superstructure ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The Complexity of Sparse Tensor PCA ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
The Difficulty of Passive Learning in Deep Reinforcement Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
The Elastic Lottery Ticket Hypothesis ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
The Emergence of Objectness: Learning Zero-shot Segmentation from Videos ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
The Image Local Autoregressive Transformer ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
The Implicit Bias of Minima Stability: A View from Function Space ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The Inductive Bias of Quantum Kernels ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
The Lazy Online Subgradient Algorithm is Universal on Strongly Convex Domains ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
The Limits of Optimal Pricing in the Dark ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The Many Faces of Adversarial Risk ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
The Pareto Frontier of model selection for general Contextual Bandits ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
The Role of Global Labels in Few-Shot Classification and How to Infer Them ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
The Semi-Random Satisfaction of Voting Axioms ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
The Skellam Mechanism for Differentially Private Federated Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
The Value of Information When Deciding What to Learn ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The balancing principle for parameter choice in distance-regularized domain adaptation ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
The future is log-Gaussian: ResNets and their infinite-depth-and-width limit at initialization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The staircase property: How hierarchical structure can guide deep learning ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Think Big, Teach Small: Do Language Models Distil Occam’s Razor? ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Three-dimensional spike localization and improved motion correction for Neuropixels recordings ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Tighter Expected Generalization Error Bounds via Wasserstein Distance ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Time-independent Generalization Bounds for SGLD in Non-convex Settings ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Time-series Generation by Contrastive Imitation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
To The Point: Correspondence-driven monocular 3D category reconstruction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
TokenLearner: Adaptive Space-Time Tokenization for Videos ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Topic Modeling Revisited: A Document Graph-based Neural Network Perspective ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
TopicNet: Semantic Graph-Guided Topic Discovery ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Topographic VAEs learn Equivariant Capsules ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Topological Attention for Time Series Forecasting ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Topological Detection of Trojaned Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Topological Relational Learning on Graphs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Topology-Imbalance Learning for Semi-Supervised Node Classification ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Towards Best-of-All-Worlds Online Learning with Feedback Graphs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Towards Biologically Plausible Convolutional Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Towards Context-Agnostic Learning Using Synthetic Data ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Towards Deeper Deep Reinforcement Learning with Spectral Normalization ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Towards Efficient and Effective Adversarial Training ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Towards Enabling Meta-Learning from Target Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Towards Lower Bounds on the Depth of ReLU Neural Networks ❌ ❌ ❌ ❌ ❌ ✅ ❌ 1
Towards Multi-Grained Explainability for Graph Neural Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
Towards Robust Bisimulation Metric Learning ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Towards Robust and Reliable Algorithmic Recourse ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors ✅ ❌ ❌ ❌ ✅ ✅ ✅ 4
Towards Sample-efficient Overparameterized Meta-learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Towards Sharper Generalization Bounds for Structured Prediction ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Towards Stable and Robust AdderNets ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Towards Tight Communication Lower Bounds for Distributed Optimisation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Towards a Theoretical Framework of Out-of-Distribution Generalization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Towards a Unified Information-Theoretic Framework for Generalization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Towards mental time travel: a hierarchical memory for reinforcement learning agents ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Towards optimally abstaining from prediction with OOD test examples ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Towards robust vision by multi-task learning on monkey visual cortex ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Towards understanding retrosynthesis by energy-based models ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
Tracking People with 3D Representations ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Tracking Without Re-recognition in Humans and Machines ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Tractable Regularization of Probabilistic Circuits ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Training Neural Networks is ER-complete ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Training Neural Networks with Fixed Sparse Masks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Training Over-parameterized Models with Non-decomposable Objectives ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Transformer in Transformer ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
TransformerFusion: Monocular RGB Scene Reconstruction using Transformers ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Tree in Tree: from Decision Trees to Decision Graphs ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
TriBERT: Human-centric Audio-visual Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
True Few-Shot Learning with Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Truncated Marginal Neural Ratio Estimation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Turing Completeness of Bounded-Precision Recurrent Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Twice regularized MDPs and the equivalence between robustness and regularization ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Twins: Revisiting the Design of Spatial Attention in Vision Transformers ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Two steps to risk sensitivity ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Two-sided fairness in rankings via Lorenz dominance ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
UCB-based Algorithms for Multinomial Logistic Regression Bandits ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Ultrahyperbolic Neural Networks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Unadversarial Examples: Designing Objects for Robust Vision ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Uncertain Decisions Facilitate Better Preference Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Uncertainty Calibration for Ensemble-Based Debiasing Methods ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Uncertainty Quantification and Deep Ensembles ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Uncertainty-Driven Loss for Single Image Super-Resolution ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Understanding Adaptive, Multiscale Temporal Integration In Deep Speech Recognition Systems ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Understanding Bandits with Graph Feedback ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Understanding Deflation Process in Over-parametrized Tensor Decomposition ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Understanding How Encoder-Decoder Architectures Attend ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Understanding Instance-based Interpretability of Variational Auto-Encoders ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Understanding Interlocking Dynamics of Cooperative Rationalization ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Understanding Partial Multi-Label Learning via Mutual Information ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
Understanding and Improving Early Stopping for Learning with Noisy Labels ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Understanding the Effect of Stochasticity in Policy Optimization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Understanding the Generalization Benefit of Model Invariance from a Data Perspective ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Understanding the Under-Coverage Bias in Uncertainty Estimation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Unfolding Taylor's Approximations for Image Restoration ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
UniDoc: Unified Pretraining Framework for Document Understanding ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Uniform Concentration Bounds toward a Unified Framework for Robust Clustering ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Uniform Sampling over Episode Difficulty ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Unifying lower bounds on prediction dimension of convex surrogates ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Unintended Selection: Persistent Qualification Rate Disparities and Interventions ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Unique sparse decomposition of low rank matrices ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Universal Approximation Using Well-Conditioned Normalizing Flows ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Universal Graph Convolutional Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Universal Off-Policy Evaluation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Universal Rate-Distortion-Perception Representations for Lossy Compression ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Universal Semi-Supervised Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Unlabeled Principal Component Analysis ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Unsupervised Foreground Extraction via Deep Region Competition ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Unsupervised Learning of Compositional Energy Concepts ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Unsupervised Motion Representation Learning with Capsule Autoencoders ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Unsupervised Noise Adaptive Speech Enhancement by Discriminator-Constrained Optimal Transport ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Unsupervised Object-Based Transition Models For 3D Partially Observable Environments ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Unsupervised Object-Level Representation Learning from Scene Images ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Unsupervised Part Discovery from Contrastive Reconstruction ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Unsupervised Representation Transfer for Small Networks: I Believe I Can Distill On-the-Fly ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Unsupervised Speech Recognition ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
User-Level Differentially Private Learning via Correlated Sampling ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
VAST: Value Function Factorization with Variable Agent Sub-Teams ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Validation Free and Replication Robust Volume-based Data Valuation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Variance-Aware Off-Policy Evaluation with Linear Function Approximation ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Variational Bayesian Optimistic Sampling ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Variational Bayesian Reinforcement Learning with Regret Bounds ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Variational Continual Bayesian Meta-Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Variational Diffusion Models ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Variational Inference for Continuous-Time Switching Dynamical Systems ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Variational Model Inversion Attacks ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Variational Multi-Task Learning with Gumbel-Softmax Priors ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Video Instance Segmentation using Inter-Frame Communication Transformers ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Visual Adversarial Imitation Learning using Variational Models ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Visualizing the Emergence of Intermediate Visual Patterns in DNNs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
VoiceMixer: Adversarial Voice Style Mixup ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Volume Rendering of Neural Implicit Surfaces ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Weak-shot Fine-grained Classification via Similarity Transfer ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Weighted model estimation for offline model-based reinforcement learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Weisfeiler and Lehman Go Cellular: CW Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Well-tuned Simple Nets Excel on Tabular Datasets ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
What Makes Multi-Modal Learning Better than Single (Provably) ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
What Matters for Adversarial Imitation Learning? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
What can linearized neural networks actually say about generalization? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
What training reveals about neural network complexity ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
What’s a good imputation to predict with missing values? ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
When Are Solutions Connected in Deep Networks? ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite Ranking ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
When Is Generalizable Reinforcement Learning Tractable? ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
When Is Unsupervised Disentanglement Possible? ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting ✅ ❌ ✅ ❌ ✅ ❌ ❌ 3
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Who Leads and Who Follows in Strategic Classification? ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Why Do Better Loss Functions Lead to Less Transferable Features? ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Why Spectral Normalization Stabilizes GANs: Analysis and Improvements ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Width-based Lookaheads with Learnt Base Policies and Heuristics Over the Atari-2600 Benchmark ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Word2Fun: Modelling Words as Functions for Diachronic Word Representation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
XCiT: Cross-Covariance Image Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
XDO: A Double Oracle Algorithm for Extensive-Form Games ✅ ✅ ❌ ❌ ❌ ❌ ❌ 2
You Are the Best Reviewer of Your Own Papers: An Owner-Assisted Scoring Mechanism ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
You Never Cluster Alone ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Your head is there to move you around: Goal-driven models of the primate dorsal pathway ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
argmax centroid ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4