reproducibilityindex.ai

International Conference on Learning Representations (ICLR) - 2022

Conference Proceedings:

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

$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
$\mathrm{SO}(2)$-Equivariant Reinforcement Learning ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
$\pi$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
8-bit Optimizers via Block-wise Quantization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease ❌ ❌ ❌ ✅ ✅ ✅ ✅ 4
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
A Comparison of Hamming Errors of Representative Variable Selection Methods ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
A Deep Variational Approach to Clustering Survival Data ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
A Fine-Grained Analysis on Distribution Shift ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
A Fine-Tuning Approach to Belief State Modeling ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A First-Occupancy Representation for Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
A General Analysis of Example-Selection for Stochastic Gradient Descent ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
A Generalized Weighted Optimization Method for Computational Learning and Inversion ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A Johnson-Lindenstrauss Framework for Randomly Initialized CNNs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Loss Curvature Perspective on Training Instabilities of Deep Learning Models ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
A NON-PARAMETRIC REGRESSION VIEWPOINT : GENERALIZATION OF OVERPARAMETRIZED DEEP RELU NETWORK UNDER NOISY OBSERVATIONS ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
A Neural Tangent Kernel Perspective of Infinite Tree Ensembles ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?" ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
A Program to Build E(N)-Equivariant Steerable CNNs ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks ✅ ❌ ✅ ✅ ✅ ✅ ❌ 5
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
A Theory of Tournament Representations ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A Zest of LIME: Towards Architecture-Independent Model Distances ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
A fast and accurate splitting method for optimal transport: analysis and implementation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
A generalization of the randomized singular value decomposition ✅ ❌ ❌ ❌ ✅ ✅ ✅ 4
A global convergence theory for deep ReLU implicit networks via over-parameterization ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
AS-MLP: An Axial Shifted MLP Architecture for Vision ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Accelerated Policy Learning with Parallel Differentiable Simulation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Acceleration of Federated Learning with Alleviated Forgetting in Local Training ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Active Hierarchical Exploration with Stable Subgoal Representation Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Actor-Critic Policy Optimization in a Large-Scale Imperfect-Information Game ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Actor-critic is implicitly biased towards high entropy optimal policies ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
AdaAug: Learning Class- and Instance-adaptive Data Augmentation Policies ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Adaptive Wavelet Transformer Network for 3D Shape Representation Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Adversarial Retriever-Ranker for Dense Text Retrieval ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Adversarial Robustness Through the Lens of Causality ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Adversarial Support Alignment ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Adversarial Unlearning of Backdoors via Implicit Hypergradient ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Adversarially Robust Conformal Prediction ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
AlphaZero-based Proof Cost Network to Aid Game Solving ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Amortized Implicit Differentiation for Stochastic Bilevel Optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
An Agnostic Approach to Federated Learning with Class Imbalance ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
An Experimental Design Perspective on Model-Based Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
An Explanation of In-context Learning as Implicit Bayesian Inference ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
An Information Fusion Approach to Learning with Instance-Dependent Label Noise ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
An Operator Theoretic View On Pruning Deep Neural Networks ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
An Unconstrained Layer-Peeled Perspective on Neural Collapse ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Ancestral protein sequence reconstruction using a tree-structured Ornstein-Uhlenbeck variational autoencoder ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Anisotropic Random Feature Regression in High Dimensions ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Anomaly Detection for Tabular Data with Internal Contrastive Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Anti-Concentrated Confidence Bonuses For Scalable Exploration ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Anytime Dense Prediction with Confidence Adaptivity ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Approximation and Learning with Deep Convolutional Models: a Kernel Perspective ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Assessing Generalization of SGD via Disagreement ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Associated Learning: an Alternative to End-to-End Backpropagation that Works on CNN, RNN, and Transformer ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Asymmetry Learning for Counterfactually-invariant Classification in OOD Tasks ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Attacking deep networks with surrogate-based adversarial black-box methods is easy ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Attention-based Interpretability with Concept Transformers ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Augmented Sliced Wasserstein Distances ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Auto-Transfer: Learning to Route Transferable Representations ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Auto-scaling Vision Transformers without Training ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Automated Self-Supervised Learning for Graphs ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Autonomous Learning of Object-Centric Abstractions for High-Level Planning ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
Autonomous Reinforcement Learning: Formalism and Benchmarking ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Autoregressive Diffusion Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Autoregressive Quantile Flows for Predictive Uncertainty Estimation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
BAM: Bayes with Adaptive Memory ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
BEiT: BERT Pre-Training of Image Transformers ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Backdoor Defense via Decoupling the Training Process ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Bag of Instances Aggregation Boosts Self-supervised Distillation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Bayesian Framework for Gradient Leakage ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Bayesian Neural Network Priors Revisited ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Benchmarking the Spectrum of Agent Capabilities ❌ ✅ ✅ ❌ ❌ ✅ ❌ 3
Better Supervisory Signals by Observing Learning Paths ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Bi-linear Value Networks for Multi-goal Reinforcement Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
BiBERT: Accurate Fully Binarized BERT ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Boosted Curriculum Reinforcement Learning ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Boosting Randomized Smoothing with Variance Reduced Classifiers ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Boosting the Certified Robustness of L-infinity Distance Nets ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Bootstrapped Meta-Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Bootstrapping Semantic Segmentation with Regional Contrast ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Bregman Gradient Policy Optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Bridging Recommendation and Marketing via Recurrent Intensity Modeling ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
CKConv: Continuous Kernel Convolution For Sequential Data ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
CURVATURE-GUIDED DYNAMIC SCALE NETWORKS FOR MULTI-VIEW STEREO ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Can an Image Classifier Suffice For Action Recognition? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Capturing Structural Locality in Non-parametric Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Case-based reasoning for better generalization in textual reinforcement learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Causal Contextual Bandits with Targeted Interventions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Chemical-Reaction-Aware Molecule Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Chunked Autoregressive GAN for Conditional Waveform Synthesis ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Churn Reduction via Distillation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Clean Images are Hard to Reblur: Exploiting the Ill-Posed Inverse Task for Dynamic Scene Deblurring ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Closed-form Sample Probing for Learning Generative Models in Zero-shot Learning ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
CoBERL: Contrastive BERT for Reinforcement Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
CoMPS: Continual Meta Policy Search ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Coherence-based Label Propagation over Time Series for Accelerated Active Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Collapse by Conditioning: Training Class-conditional GANs with Limited Data ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
ComPhy: Compositional Physical Reasoning of Objects and Events from Videos ❌ ❌ ✅ ✅ ✅ ❌ ❌ 3
Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Comparing Distributions by Measuring Differences that Affect Decision Making ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Compositional Attention: Disentangling Search and Retrieval ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Compositional Training for End-to-End Deep AUC Maximization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Concurrent Adversarial Learning for Large-Batch Training ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Conditional Contrastive Learning with Kernel ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Conditional Image Generation by Conditioning Variational Auto-Encoders ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Conditional Object-Centric Learning from Video ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Conditioning Sequence-to-sequence Networks with Learned Activations ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Connectome-constrained Latent Variable Model of Whole-Brain Neural Activity ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Consistent Counterfactuals for Deep Models ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Constrained Physical-Statistics Models for Dynamical System Identification and Prediction ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Constrained Policy Optimization via Bayesian World Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Constraining Linear-chain CRFs to Regular Languages ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Constructing Orthogonal Convolutions in an Explicit Manner ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Constructing a Good Behavior Basis for Transfer using Generalized Policy Updates ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Context-Aware Sparse Deep Coordination Graphs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Contextualized Scene Imagination for Generative Commonsense Reasoning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Continual Learning with Filter Atom Swapping ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Continual Learning with Recursive Gradient Optimization ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Continual Normalization: Rethinking Batch Normalization for Online Continual Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Continuous-Time Meta-Learning with Forward Mode Differentiation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Contrastive Fine-grained Class Clustering via Generative Adversarial Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Controlling Directions Orthogonal to a Classifier ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Controlling the Complexity and Lipschitz Constant improves Polynomial Nets ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Convergent Graph Solvers ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Convergent and Efficient Deep Q Learning Algorithm ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Coordination Among Neural Modules Through a Shared Global Workspace ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Counterfactual Plans under Distributional Ambiguity ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Creating Training Sets via Weak Indirect Supervision ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Critical Points in Quantum Generative Models ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Cross-Domain Imitation Learning via Optimal Transport ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Cross-Lingual Transfer with Class-Weighted Language-Invariant Representations ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
CrossBeam: Learning to Search in Bottom-Up Program Synthesis ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
CrossMatch: Cross-Classifier Consistency Regularization for Open-Set Single Domain Generalization ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning ❌ ✅ ✅ ❌ ❌ ✅ ✅ 4
Crystal Diffusion Variational Autoencoder for Periodic Material Generation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Curriculum learning as a tool to uncover learning principles in the brain ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
CycleMLP: A MLP-like Architecture for Dense Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
D-CODE: Discovering Closed-form ODEs from Observed Trajectories ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
DEGREE: Decomposition Based Explanation for Graph Neural Networks ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
DISCOVERING AND EXPLAINING THE REPRESENTATION BOTTLENECK OF DNNS ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
DIVA: Dataset Derivative of a Learning Task ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
DKM: Differentiable k-Means Clustering Layer for Neural Network Compression ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Data Efficient Language-Supervised Zero-Shot Recognition with Optimal Transport Distillation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Data Poisoning Won’t Save You From Facial Recognition ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Data-Driven Offline Optimization for Architecting Hardware Accelerators ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
Data-Efficient Graph Grammar Learning for Molecular Generation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
DeSKO: Stability-Assured Robust Control with a Deep Stochastic Koopman Operator ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Dealing with Non-Stationarity in MARL via Trust-Region Decomposition ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Declarative nets that are equilibrium models ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Deconstructing the Inductive Biases of Hamiltonian Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Decoupled Adaptation for Cross-Domain Object Detection ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Deep Attentive Variational Inference ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Deep AutoAugment ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Deep Point Cloud Reconstruction ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Deep ReLU Networks Preserve Expected Length ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Defending Against Image Corruptions Through Adversarial Augmentations ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Delaunay Component Analysis for Evaluation of Data Representations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Denoising Likelihood Score Matching for Conditional Score-based Data Generation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
DictFormer: Tiny Transformer with Shared Dictionary ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Differentiable DAG Sampling ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Differentiable Expectation-Maximization for Set Representation Learning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Differentiable Scaffolding Tree for Molecule Optimization ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Differentially Private Fine-tuning of Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Discovering Invariant Rationales for Graph Neural Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Discovering Latent Concepts Learned in BERT ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Discrepancy-Based Active Learning for Domain Adaptation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Discrete Representations Strengthen Vision Transformer Robustness ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Discriminative Similarity for Data Clustering ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Disentanglement Analysis with Partial Information Decomposition ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Distribution Compression in Near-Linear Time ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Distributional Reinforcement Learning with Monotonic Splines ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Distributionally Robust Fair Principal Components via Geodesic Descents ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Distributionally Robust Models with Parametric Likelihood Ratios ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Dive Deeper Into Integral Pose Regression ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Divergence-aware Federated Self-Supervised Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Diverse Client Selection for Federated Learning via Submodular Maximization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Divisive Feature Normalization Improves Image Recognition Performance in AlexNet ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Do We Need Anisotropic Graph Neural Networks? ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Do deep networks transfer invariances across classes? ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Domain Adversarial Training: A Game Perspective ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Domino: Discovering Systematic Errors with Cross-Modal Embeddings ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Dropout Q-Functions for Doubly Efficient Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Dual Lottery Ticket Hypothesis ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Dynamic Token Normalization improves Vision Transformers ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Dynamics-Aware Comparison of Learned Reward Functions ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
EViT: Expediting Vision Transformers via Token Reorganizations ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Effect of scale on catastrophic forgetting in neural networks ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
Effective Model Sparsification by Scheduled Grow-and-Prune Methods ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Efficient Active Search for Combinatorial Optimization Problems ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Efficient Neural Causal Discovery without Acyclicity Constraints ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Efficient Self-supervised Vision Transformers for Representation Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Efficient and Differentiable Conformal Prediction with General Function Classes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Efficiently Modeling Long Sequences with Structured State Spaces ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
EigenGame Unloaded: When playing games is better than optimizing ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Einops: Clear and Reliable Tensor Manipulations with Einstein-like Notation ❌ ✅ ❌ ❌ ✅ ✅ ✅ 4
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Emergent Communication at Scale ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Enabling Arbitrary Translation Objectives with Adaptive Tree Search ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
End-to-End Learning of Probabilistic Hierarchies on Graphs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Energy-Inspired Molecular Conformation Optimization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Enhancing Cross-lingual Transfer by Manifold Mixup ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
EntQA: Entity Linking as Question Answering ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Entroformer: A Transformer-based Entropy Model for Learned Image Compression ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Environment Predictive Coding for Visual Navigation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Equivariant Graph Mechanics Networks with Constraints ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Equivariant Subgraph Aggregation Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Equivariant Transformers for Neural Network based Molecular Potentials ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Evaluating Disentanglement of Structured Representations ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Evaluating Distributional Distortion in Neural Language Modeling ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Evaluating Model-Based Planning and Planner Amortization for Continuous Control ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Evidential Turing Processes ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Evolutionary Diversity Optimization with Clustering-based Selection for Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Explainable GNN-Based Models over Knowledge Graphs ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Explaining Point Processes by Learning Interpretable Temporal Logic Rules ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Explanations of Black-Box Models based on Directional Feature Interactions ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Exploiting Class Activation Value for Partial-Label Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Exploring Memorization in Adversarial Training ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Exploring extreme parameter compression for pre-trained language models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Exploring the Limits of Large Scale Pre-training ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Expressiveness and Approximation Properties of Graph Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Expressivity of Emergent Languages is a Trade-off between Contextual Complexity and Unpredictability ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Extending the WILDS Benchmark for Unsupervised Adaptation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
FILIP: Fine-grained Interactive Language-Image Pre-Training ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
FILM: Following Instructions in Language with Modular Methods ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
FP-DETR: Detection Transformer Advanced by Fully Pre-training ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Fair Normalizing Flows ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
FairCal: Fairness Calibration for Face Verification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Fairness Guarantees under Demographic Shift ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Fairness in Representation for Multilingual NLP: Insights from Controlled Experiments on Conditional Language Modeling ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Fast AdvProp ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Fast Differentiable Matrix Square Root ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Fast Generic Interaction Detection for Model Interpretability and Compression ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Fast Model Editing at Scale ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Fast Regression for Structured Inputs ✅ ❌ ❌ ❌ ✅ ✅ ✅ 4
Fast topological clustering with Wasserstein distance ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
FastSHAP: Real-Time Shapley Value Estimation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Feature Kernel Distillation ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
FedBABU: Toward Enhanced Representation for Federated Image Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Few-Shot Backdoor Attacks on Visual Object Tracking ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Few-shot Learning via Dirichlet Tessellation Ensemble ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks ❌ ✅ ✅ ❌ ❌ ✅ ✅ 4
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Fine-grained Differentiable Physics: A Yarn-level Model for Fabrics ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Finetuned Language Models are Zero-Shot Learners ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Fixed Neural Network Steganography: Train the images, not the network ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Focus on the Common Good: Group Distributional Robustness Follows ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Fooling Explanations in Text Classifiers ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Fortuitous Forgetting in Connectionist Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Frame Averaging for Invariant and Equivariant Network Design ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
GATSBI: Generative Adversarial Training for Simulation-Based Inference ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
GDA-AM: ON THE EFFECTIVENESS OF SOLVING MIN-IMAX OPTIMIZATION VIA ANDERSON MIXING ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
GLASS: GNN with Labeling Tricks for Subgraph Representation Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
GNN is a Counter? Revisiting GNN for Question Answering ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
GNN-LM: Language Modeling based on Global Contexts via GNN ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
GRAND++: Graph Neural Diffusion with A Source Term ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Gaussian Mixture Convolution Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
GeneDisco: A Benchmark for Experimental Design in Drug Discovery ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Generalisation in Lifelong Reinforcement Learning through Logical Composition ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Generalization Through the Lens of Leave-One-Out Error ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Generalized Decision Transformer for Offline Hindsight Information Matching ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Generalized Demographic Parity for Group Fairness ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generalized Kernel Thinning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Generalized rectifier wavelet covariance models for texture synthesis ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Generalizing Few-Shot NAS with Gradient Matching ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Generative Modeling with Optimal Transport Maps ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Generative Models as a Data Source for Multiview Representation Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Generative Principal Component Analysis ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Generative Pseudo-Inverse Memory ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Geometric Transformers for Protein Interface Contact Prediction ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Geometric and Physical Quantities improve E(3) Equivariant Message Passing ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
GiraffeDet: A Heavy-Neck Paradigm for Object Detection ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Givens Coordinate Descent Methods for Rotation Matrix Learning in Trainable Embedding Indexes ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Goal-Directed Planning via Hindsight Experience Replay ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
GradMax: Growing Neural Networks using Gradient Information ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
GradSign: Model Performance Inference with Theoretical Insights ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Gradient Importance Learning for Incomplete Observations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Gradient Information Matters in Policy Optimization by Back-propagating through Model ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Gradient Matching for Domain Generalization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Gradient Step Denoiser for convergent Plug-and-Play ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Granger causal inference on DAGs identifies genomic loci regulating transcription ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Graph Condensation for Graph Neural Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Graph Neural Networks with Learnable Structural and Positional Representations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Graph-Guided Network for Irregularly Sampled Multivariate Time Series ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Graph-Relational Domain Adaptation ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Graph-based Nearest Neighbor Search in Hyperbolic Spaces ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Graphon based Clustering and Testing of Networks: Algorithms and Theory ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
GreaseLM: Graph REASoning Enhanced Language Models ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Group equivariant neural posterior estimation ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
Group-based Interleaved Pipeline Parallelism for Large-scale DNN Training ❌ ❌ ✅ ❌ ✅ ✅ ✅ 4
HTLM: Hyper-Text Pre-Training and Prompting of Language Models ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Half-Inverse Gradients for Physical Deep Learning ❌ ✅ ❌ ❌ ✅ ✅ ✅ 4
Handling Distribution Shifts on Graphs: An Invariance Perspective ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Hierarchical Few-Shot Imitation with Skill Transition Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Hierarchical Variational Memory for Few-shot Learning Across Domains ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
High Probability Generalization Bounds with Fast Rates for Minimax Problems ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Hindsight Foresight Relabeling for Meta-Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Hindsight: Posterior-guided training of retrievers for improved open-ended generation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
How Attentive are Graph Attention Networks? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
How Do Vision Transformers Work? ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
How Low Can We Go: Trading Memory for Error in Low-Precision Training ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
How Much Can CLIP Benefit Vision-and-Language Tasks? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
How Well Does Self-Supervised Pre-Training Perform with Streaming Data? ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
How many degrees of freedom do we need to train deep networks: a loss landscape perspective ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
How to Train Your MAML to Excel in Few-Shot Classification ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
How to deal with missing data in supervised deep learning? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Huber Additive Models for Non-stationary Time Series Analysis ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Hybrid Local SGD for Federated Learning with Heterogeneous Communications ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Hybrid Random Features ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Hyperparameter Tuning with Renyi Differential Privacy ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
IGLU: Efficient GCN Training via Lazy Updates ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Igeood: An Information Geometry Approach to Out-of-Distribution Detection ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Illiterate DALL-E Learns to Compose ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Image BERT Pre-training with Online Tokenizer ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Imbedding Deep Neural Networks ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Imitation Learning by Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Imitation Learning from Observations under Transition Model Disparity ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Implicit Bias of Adversarial Training for Deep Neural Networks ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100 ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Improving Non-Autoregressive Translation Models Without Distillation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Improving the Accuracy of Learning Example Weights for Imbalance Classification ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Increasing the Cost of Model Extraction with Calibrated Proof of Work ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Incremental False Negative Detection for Contrastive Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Inductive Relation Prediction Using Analogy Subgraph Embeddings ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
InfinityGAN: Towards Infinite-Pixel Image Synthesis ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Information Bottleneck: Exact Analysis of (Quantized) Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Information Prioritization through Empowerment in Visual Model-based RL ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Information-theoretic Online Memory Selection for Continual Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
IntSGD: Adaptive Floatless Compression of Stochastic Gradients ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Interacting Contour Stochastic Gradient Langevin Dynamics ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Interpretable Unsupervised Diversity Denoising and Artefact Removal ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Invariant Causal Representation Learning for Out-of-Distribution Generalization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies ✅ ✅ ✅ ✅ ✅ ❌ ❌ 5
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Is High Variance Unavoidable in RL? A Case Study in Continuous Control ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Is Homophily a Necessity for Graph Neural Networks? ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Is Importance Weighting Incompatible with Interpolating Classifiers? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
It Takes Two to Tango: Mixup for Deep Metric Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Joint Shapley values: a measure of joint feature importance ❌ ✅ ✅ ❌ ✅ ❌ ❌ 3
KL Guided Domain Adaptation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Know Thyself: Transferable Visual Control Policies Through Robot-Awareness ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Know Your Action Set: Learning Action Relations for Reinforcement Learning ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Knowledge Infused Decoding ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Knowledge Removal in Sampling-based Bayesian Inference ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
L0-Sparse Canonical Correlation Analysis ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5 ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
LOSSY COMPRESSION WITH DISTRIBUTION SHIFT AS ENTROPY CONSTRAINED OPTIMAL TRANSPORT ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Label Encoding for Regression Networks ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Label Leakage and Protection in Two-party Split Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Label-Efficient Semantic Segmentation with Diffusion Models ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Language model compression with weighted low-rank factorization ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Language modeling via stochastic processes ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Language-biased image classification: evaluation based on semantic representations ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Language-driven Semantic Segmentation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Large Language Models Can Be Strong Differentially Private Learners ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Large-Scale Representation Learning on Graphs via Bootstrapping ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Latent Image Animator: Learning to Animate Images via Latent Space Navigation ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learnability of convolutional neural networks for infinite dimensional input via mixed and anisotropic smoothness ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Learned Simulators for Turbulence ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning Altruistic Behaviours in Reinforcement Learning without External Rewards ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning Causal Models from Conditional Moment Restrictions by Importance Weighting ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning Continuous Environment Fields via Implicit Functions ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Learning Curves for SGD on Structured Features ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning Distributionally Robust Models at Scale via Composite Optimization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning Efficient Online 3D Bin Packing on Packing Configuration Trees ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning Features with Parameter-Free Layers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning Generalizable Representations for Reinforcement Learning via Adaptive Meta-learner of Behavioral Similarities ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Graphon Mean Field Games and Approximate Nash Equilibria ✅ ✅ ❌ ❌ ❌ ✅ ✅ 4
Learning Hierarchical Structures with Differentiable Nondeterministic Stacks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning Long-Term Reward Redistribution via Randomized Return Decomposition ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Multimodal VAEs through Mutual Supervision ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning Neural Contextual Bandits through Perturbed Rewards ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning Object-Oriented Dynamics for Planning from Text ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning Optimal Conformal Classifiers ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Learning Prototype-oriented Set Representations for Meta-Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Representation from Neural Fisher Kernel with Low-rank Approximation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs ✅ ❌ ❌ ❌ ✅ ✅ ✅ 4
Learning State Representations via Retracing in Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Strides in Convolutional Neural Networks ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Learning Super-Features for Image Retrieval ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning Synthetic Environments and Reward Networks for Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Learning Temporally Causal Latent Processes from General Temporal Data ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Learning Towards The Largest Margins ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning Transferable Reward for Query Object Localization with Policy Adaptation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning Value Functions from Undirected State-only Experience ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning Versatile Neural Architectures by Propagating Network Codes ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Learning Weakly-supervised Contrastive Representations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning a subspace of policies for online adaptation in Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning by Directional Gradient Descent ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning meta-features for AutoML ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning more skills through optimistic exploration ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning to Annotate Part Segmentation with Gradient Matching ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning to Complete Code with Sketches ✅ ❌ ❌ ✅ ✅ ✅ ✅ 5
Learning to Dequantise with Truncated Flows ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning to Downsample for Segmentation of Ultra-High Resolution Images ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning to Extend Molecular Scaffolds with Structural Motifs ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Learning to Generalize across Domains on Single Test Samples ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning to Guide and to be Guided in the Architect-Builder Problem ✅ ✅ ❌ ✅ ✅ ❌ ✅ 5
Learning to Map for Active Semantic Goal Navigation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning to Schedule Learning rate with Graph Neural Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning transferable motor skills with hierarchical latent mixture policies ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning-Augmented $k$-means Clustering ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Leveraging Automated Unit Tests for Unsupervised Code Translation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Leveraging unlabeled data to predict out-of-distribution performance ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Linking Emergent and Natural Languages via Corpus Transfer ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Lipschitz-constrained Unsupervised Skill Discovery ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
LoRA: Low-Rank Adaptation of Large Language Models ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Local Feature Swapping for Generalization in Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Long Expressive Memory for Sequence Modeling ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Looking Back on Learned Experiences For Class/task Incremental Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Lossless Compression with Probabilistic Circuits ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
MAML is a Noisy Contrastive Learner in Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
MT3: Multi-Task Multitrack Music Transcription ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Mapping Language Models to Grounded Conceptual Spaces ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Mapping conditional distributions for domain adaptation under generalized target shift ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Maximizing Ensemble Diversity in Deep Reinforcement Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Maximum Entropy RL (Provably) Solves Some Robust RL Problems ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Maximum n-times Coverage for Vaccine Design ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Measuring CLEVRness: Black-box Testing of Visual Reasoning Models ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Memorizing Transformers ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Memory Augmented Optimizers for Deep Learning ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Memory Replay with Data Compression for Continual Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Message Passing Neural PDE Solvers ✅ ✅ ❌ ✅ ✅ ❌ ✅ 5
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Meta-Imitation Learning by Watching Video Demonstrations ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
Meta-Learning with Fewer Tasks through Task Interpolation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
MetaMorph: Learning Universal Controllers with Transformers ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Minimax Optimization with Smooth Algorithmic Adversaries ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Mirror Descent Policy Optimization ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Missingness Bias in Model Debugging ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
MoReL: Multi-omics Relational Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Model Agnostic Interpretability for Multiple Instance Learning ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Model Zoo: A Growing Brain That Learns Continually ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Model-Based Offline Meta-Reinforcement Learning with Regularization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Model-augmented Prioritized Experience Replay ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Modeling Label Space Interactions in Multi-label Classification using Box Embeddings ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Modular Lifelong Reinforcement Learning via Neural Composition ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
MonoDistill: Learning Spatial Features for Monocular 3D Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Monotonic Differentiable Sorting Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Multi-Agent MDP Homomorphic Networks ❌ ✅ ❌ ❌ ❌ ✅ ✅ 3
Multi-Critic Actor Learning: Teaching RL Policies to Act with Style ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Multi-Mode Deep Matrix and Tensor Factorization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Multi-Stage Episodic Control for Strategic Exploration in Text Games ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Multi-Task Processes ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Multi-objective Optimization by Learning Space Partition ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Multimeasurement Generative Models ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Multitask Prompted Training Enables Zero-Shot Task Generalization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
NASPY: Automated Extraction of Automated Machine Learning Models ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
NETWORK INSENSITIVITY TO PARAMETER NOISE VIA PARAMETER ATTACK DURING TRAINING ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Natural Language Descriptions of Deep Visual Features ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Network Augmentation for Tiny Deep Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
NeuPL: Neural Population Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Neural Contextual Bandits with Deep Representation and Shallow Exploration ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Neural Deep Equilibrium Solvers ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Link Prediction with Walk Pooling ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Neural Methods for Logical Reasoning over Knowledge Graphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Models for Output-Space Invariance in Combinatorial Problems ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Neural Network Approximation based on Hausdorff distance of Tropical Zonotopes ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
Neural Networks as Kernel Learners: The Silent Alignment Effect ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Neural Parameter Allocation Search ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Processes with Stochastic Attention: Paying more attention to the context dataset ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Program Synthesis with Query ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Neural Relational Inference with Node-Specific Information ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Neural Solvers for Fast and Accurate Numerical Optimal Control ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Neural Spectral Marked Point Processes ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Neural Stochastic Dual Dynamic Programming ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Neural Structured Prediction for Inductive Node Classification ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Neural Variational Dropout Processes ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Neural graphical modelling in continuous-time: consistency guarantees and algorithms ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
New Insights on Reducing Abrupt Representation Change in Online Continual Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
No One Representation to Rule Them All: Overlapping Features of Training Methods ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Noisy Feature Mixup ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Non-Linear Operator Approximations for Initial Value Problems ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Non-Parallel Text Style Transfer with Self-Parallel Supervision ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Nonlinear ICA Using Volume-Preserving Transformations ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Normalization of Language Embeddings for Cross-Lingual Alignment ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
OBJECT DYNAMICS DISTILLATION FOR SCENE DECOMPOSITION AND REPRESENTATION ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Object Pursuit: Building a Space of Objects via Discriminative Weight Generation ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Objects in Semantic Topology ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Offline Reinforcement Learning with Implicit Q-Learning ✅ ✅ ✅ ❌ ✅ ❌ ❌ 4
Offline Reinforcement Learning with Value-based Episodic Memory ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Omni-Dimensional Dynamic Convolution ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
On Bridging Generic and Personalized Federated Learning for Image Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
On Distributed Adaptive Optimization with Gradient Compression ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
On Evaluation Metrics for Graph Generative Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On Improving Adversarial Transferability of Vision Transformers ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
On Incorporating Inductive Biases into VAEs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On Non-Random Missing Labels in Semi-Supervised Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
On Predicting Generalization using GANs ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
On Redundancy and Diversity in Cell-based Neural Architecture Search ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On Robust Prefix-Tuning for Text Classification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On feature learning in neural networks with global convergence guarantees ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
On the Certified Robustness for Ensemble Models and Beyond ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On the Connection between Local Attention and Dynamic Depth-wise Convolution ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On the Convergence of Certified Robust Training with Interval Bound Propagation ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
On the Convergence of mSGD and AdaGrad for Stochastic Optimization ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On the Existence of Universal Lottery Tickets ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
On the Importance of Difficulty Calibration in Membership Inference Attacks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On the Importance of Firth Bias Reduction in Few-Shot Classification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On the Learning and Learnability of Quasimetrics ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
On the Limitations of Multimodal VAEs ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
On the Optimal Memorization Power of ReLU Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the Pitfalls of Analyzing Individual Neurons in Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
On the Role of Neural Collapse in Transfer Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
On the Uncomputability of Partition Functions in Energy-Based Sequence Models ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the approximation properties of recurrent encoder-decoder architectures ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On the benefits of maximum likelihood estimation for Regression and Forecasting ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
On the relation between statistical learning and perceptual distances ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On the role of population heterogeneity in emergent communication ❌ ✅ ❌ ❌ ❌ ✅ ✅ 3
On-Policy Model Errors in Reinforcement Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
One After Another: Learning Incremental Skills for a Changing World ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Online Ad Hoc Teamwork under Partial Observability ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Online Adversarial Attacks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Online Coreset Selection for Rehearsal-based Continual Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Online Facility Location with Predictions ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Online Hyperparameter Meta-Learning with Hypergradient Distillation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
OntoProtein: Protein Pretraining With Gene Ontology Embedding ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Open-Set Recognition: A Good Closed-Set Classifier is All You Need ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Open-World Semi-Supervised Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Open-vocabulary Object Detection via Vision and Language Knowledge Distillation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Optimal Representations for Covariate Shift ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Optimal Transport for Causal Discovery ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Optimal Transport for Long-Tailed Recognition with Learnable Cost Matrix ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Optimization and Adaptive Generalization of Three layer Neural Networks ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Optimization inspired Multi-Branch Equilibrium Models ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Optimizer Amalgamation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Optimizing Neural Networks with Gradient Lexicase Selection ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Orchestrated Value Mapping for Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Overcoming The Spectral Bias of Neural Value Approximation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
P-Adapters: Robustly Extracting Factual Information from Language Models with Diverse Prompts ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
PAC Prediction Sets Under Covariate Shift ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
PAC-Bayes Information Bottleneck ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
PF-GNN: Differentiable particle filtering based approximation of universal graph representations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
POETREE: Interpretable Policy Learning with Adaptive Decision Trees ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Pareto Policy Adaptation ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Pareto Policy Pool for Model-based Offline Reinforcement Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Path Auxiliary Proposal for MCMC in Discrete Space ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Path Integral Sampler: A Stochastic Control Approach For Sampling ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Perceiver IO: A General Architecture for Structured Inputs & Outputs ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Permutation-Based SGD: Is Random Optimal? ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Phase Collapse in Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Phenomenology of Double Descent in Finite-Width Neural Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
PiCO: Contrastive Label Disambiguation for Partial Label Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Pix2seq: A Language Modeling Framework for Object Detection ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Planning in Stochastic Environments with a Learned Model ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Plant 'n' Seek: Can You Find the Winning Ticket? ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
PoNet: Pooling Network for Efficient Token Mixing in Long Sequences ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Poisoning and Backdooring Contrastive Learning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Policy Gradients Incorporating the Future ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Policy Smoothing for Provably Robust Reinforcement Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Policy improvement by planning with Gumbel ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Possibility Before Utility: Learning And Using Hierarchical Affordances ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Post hoc Explanations may be Ineffective for Detecting Unknown Spurious Correlation ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Practical Conditional Neural Process Via Tractable Dependent Predictions ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Practical Integration via Separable Bijective Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Pre-training Molecular Graph Representation with 3D Geometry ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Predicting Physics in Mesh-reduced Space with Temporal Attention ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Pretrained Language Model in Continual Learning: A Comparative Study ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Privacy Implications of Shuffling ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Probabilistic Implicit Scene Completion ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Procedural generalization by planning with self-supervised world models ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Programmatic Reinforcement Learning without Oracles ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Progressive Distillation for Fast Sampling of Diffusion Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Proof Artifact Co-Training for Theorem Proving with Language Models ❌ ✅ ❌ ✅ ✅ ❌ ✅ 4
Properties from mechanisms: an equivariance perspective on identifiable representation learning ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse Kinematics ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Prototype memory and attention mechanisms for few shot image generation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Prototypical Contrastive Predictive Coding ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Provable Adaptation across Multiway Domains via Representation Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Provable Learning-based Algorithm For Sparse Recovery ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Provably Robust Adversarial Examples ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Provably convergent quasistatic dynamics for mean-field two-player zero-sum games ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Proving the Lottery Ticket Hypothesis for Convolutional Neural Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Pseudo Numerical Methods for Diffusion Models on Manifolds ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
QUERY EFFICIENT DECISION BASED SPARSE ATTACKS AGAINST BLACK-BOX DEEP LEARNING MODELS ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Quadtree Attention for Vision Transformers ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Query Embedding on Hyper-Relational Knowledge Graphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
R4D: Utilizing Reference Objects for Long-Range Distance Estimation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Random matrices in service of ML footprint: ternary random features with no performance loss ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Real-Time Neural Voice Camouflage ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Recursive Disentanglement Network ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank? ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
RegionViT: Regional-to-Local Attention for Vision Transformers ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Regularized Autoencoders for Isometric Representation Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Reinforcement Learning in Presence of Discrete Markovian Context Evolution ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Relating transformers to models and neural representations of the hippocampal formation ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Relational Learning with Variational Bayes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Relational Multi-Task Learning: Modeling Relations between Data and Tasks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Relational Surrogate Loss Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
RelaxLoss: Defending Membership Inference Attacks without Losing Utility ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Reliable Adversarial Distillation with Unreliable Teachers ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Representation Learning for Online and Offline RL in Low-rank MDPs ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Representation-Agnostic Shape Fields ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Representational Continuity for Unsupervised Continual Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Resolving Training Biases via Influence-based Data Relabeling ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Responsible Disclosure of Generative Models Using Scalable Fingerprinting ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Rethinking Adversarial Transferability from a Data Distribution Perspective ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Rethinking Class-Prior Estimation for Positive-Unlabeled Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Rethinking Goal-Conditioned Supervised Learning and Its Connection to Offline RL ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Rethinking Supervised Pre-Training for Better Downstream Transferring ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Reverse Engineering of Imperceptible Adversarial Image Perturbations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Revisiting Design Choices in Offline Model Based Reinforcement Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Revisiting Over-smoothing in BERT from the Perspective of Graph ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Revisiting flow generative models for Out-of-distribution detection ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Reward Uncertainty for Exploration in Preference-based Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Robust and Scalable SDE Learning: A Functional Perspective ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
RotoGrad: Gradient Homogenization in Multitask Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
RvS: What is Essential for Offline RL via Supervised Learning? ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
SGD Can Converge to Local Maxima ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
SPIRAL: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Training ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
SUMNAS: Supernet with Unbiased Meta-Features for Neural Architecture Search ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Safe Neurosymbolic Learning with Differentiable Symbolic Execution ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Salient ImageNet: How to discover spurious features in Deep Learning? ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Sample and Computation Redistribution for Efficient Face Detection ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Sampling with Mirrored Stein Operators ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Scalable Sampling for Nonsymmetric Determinantal Point Processes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Scale Efficiently: Insights from Pretraining and Finetuning Transformers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Scale Mixtures of Neural Network Gaussian Processes ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Scaling Laws for Neural Machine Translation ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Scarf: Self-Supervised Contrastive Learning using Random Feature Corruption ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Selective Ensembles for Consistent Predictions ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
Self-Joint Supervised Learning ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Self-Supervised Inference in State-Space Models ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Self-Supervision Enhanced Feature Selection with Correlated Gates ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Self-ensemble Adversarial Training for Improved Robustness ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Self-supervised Learning is More Robust to Dataset Imbalance ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Should I Run Offline Reinforcement Learning or Behavioral Cloning? ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Shuffle Private Stochastic Convex Optimization ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Signing the Supermask: Keep, Hide, Invert ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
SketchODE: Learning neural sketch representation in continuous time ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Skill-based Meta-Reinforcement Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Sound Adversarial Audio-Visual Navigation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Sound and Complete Neural Network Repair with Minimality and Locality Guarantees ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Space-Time Graph Neural Networks ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
Spanning Tree-based Graph Generation for Molecules ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Sparse Attention with Learning to Hash ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Sparse Communication via Mixed Distributions ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
SphereFace2: Binary Classification is All You Need for Deep Face Recognition ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Spherical Message Passing for 3D Molecular Graphs ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Spike-inspired rank coding for fast and accurate recurrent neural networks ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Sqrt(d) Dimension Dependence of Langevin Monte Carlo ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Stability Regularization for Discrete Representation Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Steerable Partial Differential Operators for Equivariant Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Stein Latent Optimization for Generative Adversarial Networks ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Step-unrolled Denoising Autoencoders for Text Generation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Stiffness-aware neural network for learning Hamiltonian systems ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Stochastic Training is Not Necessary for Generalization ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Strength of Minibatch Noise in SGD ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
StyleAlign: Analysis and Applications of Aligned StyleGAN Models ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
StyleNeRF: A Style-based 3D Aware Generator for High-resolution Image Synthesis ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Subspace Regularizers for Few-Shot Class Incremental Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Surreal-GAN:Semi-Supervised Representation Learning via GAN for uncovering heterogeneous disease-related imaging patterns ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Surrogate Gap Minimization Improves Sharpness-Aware Training ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Switch to Generalize: Domain-Switch Learning for Cross-Domain Few-Shot Classification ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Symbolic Learning to Optimize: Towards Interpretability and Scalability ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Synchromesh: Reliable Code Generation from Pre-trained Language Models ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
TAPEX: Table Pre-training via Learning a Neural SQL Executor ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
TAda! Temporally-Adaptive Convolutions for Video Understanding ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
TPU-GAN: Learning temporal coherence from dynamic point cloud sequences ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
TRGP: Trust Region Gradient Projection for Continual Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Taming Sparsely Activated Transformer with Stochastic Experts ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Target-Side Input Augmentation for Sequence to Sequence Generation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Task Affinity with Maximum Bipartite Matching in Few-Shot Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Task Relatedness-Based Generalization Bounds for Meta Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Task-Induced Representation Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
The Close Relationship Between Contrastive Learning and Meta-Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
The Efficiency Misnomer ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
The Evolution of Uncertainty of Learning in Games ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
The Information Geometry of Unsupervised Reinforcement Learning ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
The MultiBERTs: BERT Reproductions for Robustness Analysis ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
The Role of Pretrained Representations for the OOD Generalization of RL Agents ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
The Spectral Bias of Polynomial Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The Three Stages of Learning Dynamics in High-dimensional Kernel Methods ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The Uncanny Similarity of Recurrence and Depth ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Tighter Sparse Approximation Bounds for ReLU Neural Networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Top-N: Equivariant Set and Graph Generation without Exchangeability ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Top-label calibration and multiclass-to-binary reductions ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Topological Experience Replay ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Topological Graph Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Topologically Regularized Data Embeddings ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Toward Efficient Low-Precision Training: Data Format Optimization and Hysteresis Quantization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Toward Faithful Case-based Reasoning through Learning Prototypes in a Nearest Neighbor-friendly Space. ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Towards Building A Group-based Unsupervised Representation Disentanglement Framework ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Towards Continual Knowledge Learning of Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Towards Empirical Sandwich Bounds on the Rate-Distortion Function ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Towards Evaluating the Robustness of Neural Networks Learned by Transduction ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Towards General Function Approximation in Zero-Sum Markov Games ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Towards Model Agnostic Federated Learning Using Knowledge Distillation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Towards Understanding Generalization via Decomposing Excess Risk Dynamics ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Towards Understanding the Data Dependency of Mixup-style Training ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Towards Understanding the Robustness Against Evasion Attack on Categorical Data ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Towards a Unified View of Parameter-Efficient Transfer Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Tracking the risk of a deployed model and detecting harmful distribution shifts ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Training Structured Neural Networks Through Manifold Identification and Variance Reduction ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Training Transition Policies via Distribution Matching for Complex Tasks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Training invariances and the low-rank phenomenon: beyond linear networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Transfer RL across Observation Feature Spaces via Model-Based Regularization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Transferable Adversarial Attack based on Integrated Gradients ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Transformer Embeddings of Irregularly Spaced Events and Their Participants ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Transformer-based Transform Coding ❌ ❌ ✅ ❌ ✅ ✅ ✅ 4
Transformers Can Do Bayesian Inference ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Triangle and Four Cycle Counting with Predictions in Graph Streams ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Trigger Hunting with a Topological Prior for Trojan Detection ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Trivial or Impossible --- dichotomous data difficulty masks model differences (on ImageNet and beyond) ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Uncertainty Modeling for Out-of-Distribution Generalization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Understanding Dimensional Collapse in Contrastive Self-supervised Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Understanding Domain Randomization for Sim-to-real Transfer ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Understanding Intrinsic Robustness Using Label Uncertainty ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Understanding and Leveraging Overparameterization in Recursive Value Estimation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Understanding and Preventing Capacity Loss in Reinforcement Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Understanding approximate and unrolled dictionary learning for pattern recovery ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Understanding over-squashing and bottlenecks on graphs via curvature ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Understanding the Role of Self Attention for Efficient Speech Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Understanding the Variance Collapse of SVGD in High Dimensions ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
UniFormer: Unified Transformer for Efficient Spatial-Temporal Representation Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Unified Visual Transformer Compression ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Unifying Likelihood-free Inference with Black-box Optimization and Beyond ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Universal Approximation Under Constraints is Possible with Transformers ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
Universalizing Weak Supervision ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Unraveling Model-Agnostic Meta-Learning via The Adaptation Learning Rate ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Unrolling PALM for Sparse Semi-Blind Source Separation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Unsupervised Discovery of Object Radiance Fields ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Unsupervised Disentanglement with Tensor Product Representations on the Torus ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Unsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loop ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Unsupervised Semantic Segmentation by Distilling Feature Correspondences ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
VAE Approximation Error: ELBO and Exponential Families ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
VC dimension of partially quantized neural networks in the overparametrized regime ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
VOS: Learning What You Don't Know by Virtual Outlier Synthesis ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Value Gradient weighted Model-Based Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
Variational Neural Cellular Automata ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Variational Predictive Routing with Nested Subjective Timescales ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Variational methods for simulation-based inference ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Variational oracle guiding for reinforcement learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Vector-quantized Image Modeling with Improved VQGAN ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
ViDT: An Efficient and Effective Fully Transformer-based Object Detector ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
ViTGAN: Training GANs with Vision Transformers ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Vision-Based Manipulators Need to Also See from Their Hands ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Visual Correspondence Hallucination ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Visual Representation Learning over Latent Domains ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Visual hyperacuity with moving sensor and recurrent neural computations ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Vitruvion: A Generative Model of Parametric CAD Sketches ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
W-CTC: a Connectionist Temporal Classification Loss with Wild Cards ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Weighted Training for Cross-Task Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
What Do We Mean by Generalization in Federated Learning? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
What Makes Better Augmentation Strategies? Augment Difficult but Not too Different ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
When should agents explore? ✅ ❌ ✅ ❌ ✅ ✅ ✅ 5
When, Why, and Which Pretrained GANs Are Useful? ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
Who Is Your Right Mixup Partner in Positive and Unlabeled Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Why Propagate Alone? Parallel Use of Labels and Features on Graphs ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Zero Pixel Directional Boundary by Vector Transform ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Zero-CL: Instance and Feature decorrelation for negative-free symmetric contrastive learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Zero-Shot Self-Supervised Learning for MRI Reconstruction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
cosFormer: Rethinking Softmax In Attention ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
iFlood: A Stable and Effective Regularizer ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
miniF2F: a cross-system benchmark for formal Olympiad-level mathematics ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
switch-GLAT: Multilingual Parallel Machine Translation Via Code-Switch Decoder ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4