reproducibilityindex.ai

International Conference on Learning Representations (ICLR) - 2021

Conference Proceedings:

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

$i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
A Block Minifloat Representation for Training Deep Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
A Critique of Self-Expressive Deep Subspace Clustering ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Design Space Study for LISTA and Beyond ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Discriminative Gaussian Mixture Model with Sparsity ✅ ❌ ✅ ✅ ❌ ❌ ❌ 3
A Distributional Approach to Controlled Text Generation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
A Geometric Analysis of Deep Generative Image Models and Its Applications ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
A Good Image Generator Is What You Need for High-Resolution Video Synthesis ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
A Gradient Flow Framework For Analyzing Network Pruning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A Hypergradient Approach to Robust Regression without Correspondence ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
A Learning Theoretic Perspective on Local Explainability ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
A Temporal Kernel Approach for Deep Learning with Continuous-time Information ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
A Unified Approach to Interpreting and Boosting Adversarial Transferability ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
A Universal Representation Transformer Layer for Few-Shot Image Classification ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
A statistical theory of cold posteriors in deep neural networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
A teacher-student framework to distill future trajectories ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
A unifying view on implicit bias in training linear neural networks ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
AUXILIARY TASK UPDATE DECOMPOSITION: THE GOOD, THE BAD AND THE NEUTRAL ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Accurate Learning of Graph Representations with Graph Multiset Pooling ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Acting in Delayed Environments with Non-Stationary Markov Policies ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Activation-level uncertainty in deep neural networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Active Contrastive Learning of Audio-Visual Video Representations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
AdaSpeech: Adaptive Text to Speech for Custom Voice ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Adapting to Reward Progressivity via Spectral Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Adaptive Extra-Gradient Methods for Min-Max Optimization and Games ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Adaptive Federated Optimization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Adaptive Procedural Task Generation for Hard-Exploration Problems ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Adaptive Universal Generalized PageRank Graph Neural Network ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Adaptive and Generative Zero-Shot Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Adversarial score matching and improved sampling for image generation ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Adversarially Guided Actor-Critic ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Aligning AI With Shared Human Values ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
An Unsupervised Deep Learning Approach for Real-World Image Denoising ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Anytime Sampling for Autoregressive Models via Ordered Autoencoding ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees? ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Are wider nets better given the same number of parameters? ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Attentional Constellation Nets for Few-Shot Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Auction Learning as a Two-Player Game ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Autoregressive Entity Retrieval ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Auxiliary Learning by Implicit Differentiation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Average-case Acceleration for Bilinear Games and Normal Matrices ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
BERTology Meets Biology: Interpreting Attention in Protein Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
BOIL: Towards Representation Change for Few-shot Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
BREEDS: Benchmarks for Subpopulation Shift ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration ✅ ❌ ❌ ✅ ✅ ❌ ✅ 4
Bag of Tricks for Adversarial Training ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Balancing Constraints and Rewards with Meta-Gradient D4PG ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Batch Reinforcement Learning Through Continuation Method ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Bayesian Context Aggregation for Neural Processes ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Behavioral Cloning from Noisy Demonstrations ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Benchmarks for Deep Off-Policy Evaluation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Better Fine-Tuning by Reducing Representational Collapse ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Beyond Categorical Label Representations for Image Classification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
BiPointNet: Binary Neural Network for Point Clouds ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Blending MPC & Value Function Approximation for Efficient Reinforcement Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Byzantine-Resilient Non-Convex Stochastic Gradient Descent ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
C-Learning: Horizon-Aware Cumulative Accessibility Estimation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
C-Learning: Learning to Achieve Goals via Recursive Classification ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
CO2: Consistent Contrast for Unsupervised Visual Representation Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
CPR: Classifier-Projection Regularization for Continual Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
CPT: Efficient Deep Neural Network Training via Cyclic Precision ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
CT-Net: Channel Tensorization Network for Video Classification ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
CaPC Learning: Confidential and Private Collaborative Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Calibration of Neural Networks using Splines ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Calibration tests beyond classification ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Can a Fruit Fly Learn Word Embeddings? ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Capturing Label Characteristics in VAEs ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Categorical Normalizing Flows via Continuous Transformations ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Certify or Predict: Boosting Certified Robustness with Compositional Architectures ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Chaos of Learning Beyond Zero-sum and Coordination via Game Decompositions ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Characterizing signal propagation to close the performance gap in unnormalized ResNets ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Clairvoyance: A Pipeline Toolkit for Medical Time Series ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Class Normalization for (Continual)? Generalized Zero-Shot Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
CoCon: A Self-Supervised Approach for Controlled Text Generation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Colorization Transformer ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Combining Ensembles and Data Augmentation Can Harm Your Calibration ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Combining Label Propagation and Simple Models out-performs Graph Neural Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Combining Physics and Machine Learning for Network Flow Estimation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Communication in Multi-Agent Reinforcement Learning: Intention Sharing ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
CompOFA – Compound Once-For-All Networks for Faster Multi-Platform Deployment ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Complex Query Answering with Neural Link Predictors ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Computational Separation Between Convolutional and Fully-Connected Networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Concept Learners for Few-Shot Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Conditional Generative Modeling via Learning the Latent Space ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Conditional Negative Sampling for Contrastive Learning of Visual Representations ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Conformation-Guided Molecular Representation with Hamiltonian Neural Networks ❌ ❌ ✅ ✅ ❌ ✅ ✅ 4
Conservative Safety Critics for Exploration ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Contemplating Real-World Object Classification ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Contextual Dropout: An Efficient Sample-Dependent Dropout Module ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Contextual Transformation Networks for Online Continual Learning ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Continual learning in recurrent neural networks ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Contrastive Divergence Learning is a Time Reversal Adversarial Game ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Contrastive Learning with Hard Negative Samples ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Contrastive Syn-to-Real Generalization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Control-Aware Representations for Model-based Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Convex Regularization behind Neural Reconstruction ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Coping with Label Shift via Distributionally Robust Optimisation ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Correcting experience replay for multi-agent communication ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Counterfactual Generative Networks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Creative Sketch Generation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Cross-Attentional Audio-Visual Fusion for Weakly-Supervised Action Localization ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Cut out the annotator, keep the cutout: better segmentation with weak supervision ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DC3: A learning method for optimization with hard constraints ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DDPNOpt: Differential Dynamic Programming Neural Optimizer ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
DINO: A Conditional Energy-Based GAN for Domain Translation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
DOP: Off-Policy Multi-Agent Decomposed Policy Gradients ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Data-Efficient Reinforcement Learning with Self-Predictive Representations ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Dataset Condensation with Gradient Matching ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Dataset Inference: Ownership Resolution in Machine Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Dataset Meta-Learning from Kernel Ridge-Regression ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
DeLighT: Deep and Light-weight Transformer ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Debiasing Concept-based Explanations with Causal Analysis ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Decentralized Attribution of Generative Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Deconstructing the Regularization of BatchNorm ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Decoupling Global and Local Representations via Invertible Generative Flows ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Deep Equals Shallow for ReLU Networks in Kernel Regimes ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Deep Learning meets Projective Clustering ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Deep Networks and the Multiple Manifold Problem ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples ❌ ❌ ✅ ❌ ✅ ✅ ✅ 4
Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Deformable DETR: Deformable Transformers for End-to-End Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Degree-Quant: Quantization-Aware Training for Graph Neural Networks ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Denoising Diffusion Implicit Models ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
DiffWave: A Versatile Diffusion Model for Audio Synthesis ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Differentiable Segmentation of Sequences ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Differentiable Trust Region Layers for Deep Reinforcement Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Differentially Private Learning Needs Better Features (or Much More Data) ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Directed Acyclic Graph Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Disambiguating Symbolic Expressions in Informal Documents ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Discovering Non-monotonic Autoregressive Orderings with Variational Inference ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Discovering a set of policies for the worst case reward ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Discrete Graph Structure Learning for Forecasting Multiple Time Series ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Disentangled Recurrent Wasserstein Autoencoder ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Disentangling 3D Prototypical Networks for Few-Shot Concept Learning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Distance-Based Regularisation of Deep Networks for Fine-Tuning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Distilling Knowledge from Reader to Retriever for Question Answering ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Distributional Sliced-Wasserstein and Applications to Generative Modeling ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Diverse Video Generation using a Gaussian Process Trigger ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Does enhanced shape bias improve neural network robustness to common corruptions? ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Domain Generalization with MixStyle ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Domain-Robust Visual Imitation Learning with Mutual Information Constraints ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
DrNAS: Dirichlet Neural Architecture Search ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Dual-mode ASR: Unify and Improve Streaming ASR with Full-context Modeling ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Dynamic Tensor Rematerialization ✅ ✅ ❌ ❌ ✅ ✅ ✅ 5
ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
EEC: Learning to Encode and Regenerate Images for Continual Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
EVALUATION OF NEURAL ARCHITECTURES TRAINED WITH SQUARE LOSS VS CROSS-ENTROPY IN CLASSIFICATION TASKS ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Early Stopping in Deep Networks: Double Descent and How to Eliminate it ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Effective Abstract Reasoning with Dual-Contrast Network ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Effective Distributed Learning with Random Features: Improved Bounds and Algorithms ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Effective and Efficient Vote Attack on Capsule Networks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Efficient Certified Defenses Against Patch Attacks on Image Classifiers ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Efficient Continual Learning with Modular Networks and Task-Driven Priors ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Efficient Empowerment Estimation for Unsupervised Stabilization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Efficient Generalized Spherical CNNs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Efficient Inference of Flexible Interaction in Spiking-neuron Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation ❌ ❌ ❌ ✅ ✅ ❌ ✅ 3
Efficient Wasserstein Natural Gradients for Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
EigenGame: PCA as a Nash Equilibrium ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Emergent Road Rules In Multi-Agent Driving Environments ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Emergent Symbols through Binding in External Memory ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
End-to-End Egospheric Spatial Memory ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
End-to-end Adversarial Text-to-Speech ✅ ❌ ❌ ✅ ✅ ✅ ✅ 5
Enforcing robust control guarantees within neural network policies ✅ ✅ ❌ ✅ ✅ ❌ ✅ 5
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Entropic gradient descent algorithms and wide flat minima ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Estimating Lipschitz constants of monotone deep equilibrium models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Estimating informativeness of samples with Smooth Unique Information ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Evaluation of Similarity-based Explanations ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Evaluations and Methods for Explanation through Robustness Analysis ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Evolving Reinforcement Learning Algorithms ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Explainable Deep One-Class Classification ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Explaining the Efficacy of Counterfactually Augmented Data ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Exploring Balanced Feature Spaces for Representation Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Expressive Power of Invariant and Equivariant Graph Neural Networks ❌ ✅ ❌ ✅ ❌ ✅ ✅ 4
Extracting Strong Policies for Robotics Tasks from Zero-Order Trajectory Optimizers ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Extreme Memorization via Scale of Initialization ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Fair Mixup: Fairness via Interpolation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
FairBatch: Batch Selection for Model Fairness ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Fast And Slow Learning Of Recurrent Independent Mechanisms ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Fast Geometric Projections for Local Robustness Certification ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Fast convergence of stochastic subgradient method under interpolation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Faster Binary Embeddings for Preserving Euclidean Distances ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
FedMix: Approximation of Mixup under Mean Augmented Federated Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Federated Learning Based on Dynamic Regularization ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Few-Shot Bayesian Optimization with Deep Kernel Surrogates ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Few-Shot Learning via Learning the Representation, Provably ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Fidelity-based Deep Adiabatic Scheduling ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Filtered Inner Product Projection for Crosslingual Embedding Alignment ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Fooling a Complete Neural Network Verifier ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
For self-supervised learning, Rationality implies generalization, provably ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Fourier Neural Operator for Parametric Partial Differential Equations ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
Free Lunch for Few-shot Learning: Distribution Calibration ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
GAN "Steerability" without optimization ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
GANs Can Play Lottery Tickets Too ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Generalization bounds via distillation ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Generalization in data-driven models of primary visual cortex ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generalized Energy Based Models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Generalized Multimodal ELBO ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generalized Variational Continual Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Generating Adversarial Computer Programs using Optimized Obfuscations ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Generative Scene Graph Networks ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Generative Time-series Modeling with Fourier Flows ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning ✅ ❌ ❌ ❌ ✅ ❌ ✅ 3
Geometry-Aware Gradient Algorithms for Neural Architecture Search ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Geometry-aware Instance-reweighted Adversarial Training ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Getting a CLUE: A Method for Explaining Uncertainty Estimates ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Global Convergence of Three-layer Neural Networks in the Mean Field Regime ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Go with the flow: Adaptive control for Neural ODEs ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Gradient Origin Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Gradient Projection Memory for Continual Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Graph Coarsening with Neural Networks ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Graph Convolution with Low-rank Learnable Local Filters ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Graph Edit Networks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Graph Information Bottleneck for Subgraph Recognition ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Graph-Based Continual Learning ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
GraphCodeBERT: Pre-training Code Representations with Data Flow ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Grounded Language Learning Fast and Slow ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Grounding Language to Autonomously-Acquired Skills via Goal Generation ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Group Equivariant Conditional Neural Processes ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Group Equivariant Generative Adversarial Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Group Equivariant Stand-Alone Self-Attention For Vision ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Growing Efficient Deep Networks by Structured Continuous Sparsification ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
HalentNet: Multimodal Trajectory Forecasting with Hallucinative Intents ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Hierarchical Autoregressive Modeling for Neural Video Compression ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Hierarchical Reinforcement Learning by Discovering Intrinsic Options ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
High-Capacity Expert Binary Networks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Hopfield Networks is All You Need ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
How Benign is Benign Overfitting ? ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
How Does Mixup Help With Robustness and Generalization? ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks? ✅ ❌ ✅ ❌ ❌ ❌ ❌ 2
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Human-Level Performance in No-Press Diplomacy via Equilibrium Search ❌ ❌ ❌ ❌ ✅ ❌ ✅ 2
HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
HyperGrid Transformers: Towards A Single Model for Multiple Tasks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Hyperbolic Neural Networks++ ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
IOT: Instance-wise Layer Reordering for Transformer Structures ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Identifying Physical Law of Hamiltonian Systems via Meta-Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Impact of Representation Learning in Linear Bandits ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Implicit Gradient Regularization ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Implicit Normalizing Flows ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Improved Autoregressive Modeling with Distribution Smoothing ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Improved Estimation of Concentration Under $\ell_p$-Norm Distance Metrics Using Half Spaces ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Improving Adversarial Robustness via Channel-wise Activation Suppressing ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Improving Transformation Invariance in Contrastive Representation Learning ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Improving VAEs' Robustness to Adversarial Attack ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
In Search of Lost Domain Generalization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Incremental few-shot learning via vector quantization in deep embedded space ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Individually Fair Gradient Boosting ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
Individually Fair Rankings ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Influence Estimation for Generative Adversarial Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Influence Functions in Deep Learning Are Fragile ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Information Laundering for Model Privacy ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Initialization and Regularization of Factorized Neural Layers ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Integrating Categorical Semantics into Unsupervised Domain Translation ❌ ✅ ✅ ✅ ❌ ✅ ❌ 4
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Interpretable Models for Granger Causality Using Self-explaining Neural Networks ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Interpreting Knowledge Graph Relation Representation from Word Embeddings ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Interpreting and Boosting Dropout from a Game-Theoretic View ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Intraclass clustering: an implicit learning ability that regularizes DNNs ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Is Attention Better Than Matrix Decomposition? ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
IsarStep: a Benchmark for High-level Mathematical Reasoning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Isometric Propagation Network for Generalized Zero-shot Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Isometric Transformation Invariant and Equivariant Graph Convolutional Networks ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Isotropy in the Contextual Embedding Space: Clusters and Manifolds ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Iterated learning for emergent systematicity in VQA ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Iterative Empirical Game Solving via Single Policy Best Response ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Knowledge Distillation as Semiparametric Inference ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Knowledge distillation via softmax regression representation learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
LEAF: A Learnable Frontend for Audio Classification ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
LambdaNetworks: Modeling long-range Interactions without Attention ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Language-Agnostic Representation Learning of Source Code from Structure and Context ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Large Associative Memory Problem in Neurobiology and Machine Learning ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Large Batch Simulation for Deep Reinforcement Learning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Large-width functional asymptotics for deep Gaussian neural networks ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Latent Convergent Cross Mapping ❌ ✅ ❌ ✅ ❌ ✅ ✅ 4
Latent Skill Planning for Exploration and Transfer ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Layer-adaptive Sparsity for the Magnitude-based Pruning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learnable Embedding sizes for Recommender Systems ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning "What-if" Explanations for Sequential Decision-Making ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning A Minimax Optimizer: A Pilot Study ✅ ✅ ❌ ✅ ✅ ❌ ✅ 5
Learning Accurate Entropy Model with Global Reference for Image Compression ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Learning Associative Inference Using Fast Weight Memory ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning Deep Features in Instrumental Variable Regression ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning Energy-Based Models by Diffusion Recovery Likelihood ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Generalizable Visual Representations via Interactive Gameplay ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
Learning Hyperbolic Representations of Topological Features ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize ❌ ✅ ❌ ❌ ✅ ❌ ✅ 3
Learning Invariant Representations for Reinforcement Learning without Reconstruction ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning Long-term Visual Dynamics with Region Proposal Interaction Networks ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning Manifold Patch-Based Representations of Man-Made Shapes ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning Mesh-Based Simulation with Graph Networks ❌ ❌ ❌ ✅ ✅ ✅ ✅ 4
Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning Neural Event Functions for Ordinary Differential Equations ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Learning Neural Generative Dynamics for Molecular Conformation Generation ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Learning Parametrised Graph Shift Operators ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
Learning Robust State Abstractions for Hidden-Parameter Block MDPs ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Learning Structural Edits via Incremental Tree Transformations ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning Subgoal Representations with Slow Dynamics ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning Task Decomposition with Ordered Memory Policy Network ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning Task-General Representations with Generative Neuro-Symbolic Modeling ✅ ✅ ✅ ❌ ❌ ❌ ❌ 3
Learning Value Functions in Deep Policy Gradients using Residual Variance ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Learning What To Do by Simulating the Past ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Learning a Latent Search Space for Routing Problems using Variational Autoencoders ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Learning a Latent Simplex in Input Sparsity Time ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning advanced mathematical computations from examples ❌ ❌ ❌ ✅ ✅ ✅ ✅ 4
Learning and Evaluating Representations for Deep One-Class Classification ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning continuous-time PDEs from sparse data with graph neural networks ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Learning explanations that are hard to vary ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning from Demonstration with Weakly Supervised Disentanglement ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Learning from Protein Structure with Geometric Vector Perceptrons ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
Learning from others' mistakes: Avoiding dataset biases without modeling them ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Learning perturbation sets for robust machine learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning the Pareto Front with Hypernetworks ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Learning to Generate 3D Shapes with Generative Cellular Automata ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Learning to Make Decisions via Submodular Regularization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Learning to Reach Goals via Iterated Supervised Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning to Recombine and Resample Data For Compositional Generalization ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Learning to Represent Action Values as a Hypergraph on the Action Vertices ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning to Sample with Local and Global Contexts in Experience Replay Buffer ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Learning to Set Waypoints for Audio-Visual Navigation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning with AMIGo: Adversarially Motivated Intrinsic Goals ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Learning with Feature-Dependent Label Noise: A Progressive Approach ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Learning-based Support Estimation in Sublinear Time ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Lifelong Learning of Compositional Structures ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
LiftPool: Bidirectional ConvNet Pooling ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Linear Convergent Decentralized Optimization with Compression ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Linear Last-iterate Convergence in Constrained Saddle-point Optimization ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Linear Mode Connectivity in Multitask and Continual Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Lipschitz Recurrent Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Local Search Algorithms for Rank-Constrained Convex Optimization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Locally Free Weight Sharing for Network Width Search ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Long Range Arena : A Benchmark for Efficient Transformers ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Long-tail learning via logit adjustment ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Lossless Compression of Structured Convolutional Models via Lifting ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
MALI: A memory efficient and reverse accurate integrator for Neural ODEs ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
MIROSTAT: A NEURAL TEXT DECODING ALGORITHM THAT DIRECTLY CONTROLS PERPLEXITY ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Mapping the Timescale Organization of Neural Language Models ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Mastering Atari with Discrete World Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Mathematical Reasoning via Self-supervised Skip-tree Training ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Measuring Massive Multitask Language Understanding ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Memory Optimization for Deep Networks ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Meta Back-Translation ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Meta-Learning of Structured Task Distributions in Humans and Machines ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
Meta-Learning with Neural Tangent Kernels ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Meta-learning Symmetries by Reparameterization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Meta-learning with negative learning rates ❌ ❌ ❌ ✅ ❌ ❌ ✅ 2
MetaNorm: Learning to Normalize Few-Shot Batches Across Domains ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Mind the Pad -- CNNs Can Develop Blind Spots ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Minimum Width for Universal Approximation ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
MixKD: Towards Efficient Distillation of Large-scale Language Models ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Mixed-Features Vectors and Subspace Splitting ❌ ✅ ❌ ❌ ❌ ❌ ❌ 1
MoPro: Webly Supervised Learning with Momentum Prototypes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Model-Based Offline Planning ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Model-Based Visual Planning with Self-Supervised Functional Distances ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose? ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Modeling the Second Player in Distributionally Robust Optimization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Molecule Optimization by Explainable Evolution ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Monotonic Kronecker-Factored Lattice ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Monte-Carlo Planning and Learning with Language Action Value Estimates ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
More or Less: When and How to Build Convolutional Neural Network Ensembles ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Multi-Time Attention Networks for Irregularly Sampled Time Series ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Multi-resolution modeling of a discrete stochastic process identifies causes of cancer ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Multi-timescale Representation Learning in LSTM Language Models ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
MultiModalQA: complex question answering over text, tables and images ❌ ✅ ✅ ✅ ❌ ❌ ❌ 3
Multiplicative Filter Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Multiscale Score Matching for Out-of-Distribution Detection ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Mutual Information State Intrinsic Control ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
NBDT: Neural-Backed Decision Tree ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control ✅ ✅ ❌ ✅ ✅ ✅ ✅ 6
NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Nearest Neighbor Machine Translation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Negative Data Augmentation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Net-DNF: Effective Deep Modeling of Tabular Data ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Network Pruning That Matters: A Case Study on Retraining Variants ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Neural Approximate Sufficient Statistics for Implicit Models ✅ ✅ ❌ ✅ ❌ ❌ ✅ 4
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Delay Differential Equations ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Neural Networks for Learning Counterfactual G-Invariances from Single Environments ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Neural ODE Processes ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Neural Pruning via Growing Regularization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Neural Spatio-Temporal Point Processes ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Neural Synthesis of Binaural Speech From Mono Audio ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Neural Thompson Sampling ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Neural Topic Model via Optimal Transport ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Neural gradients are near-lognormal: improved quantized and sparse training ✅ ✅ ✅ ✅ ❌ ❌ ❌ 4
Neural networks with late-phase weights ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Neural representation and generation for RNA secondary structures ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Neurally Augmented ALISTA ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
New Bounds For Distributed Mean Estimation and Variance Reduction ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
No MCMC for me: Amortized sampling for fast and stable training of energy-based models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Noise against noise: stochastic label noise helps combat inherent label noise ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Noise or Signal: The Role of Image Backgrounds in Object Recognition ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Nonseparable Symplectic Neural Networks ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On Data-Augmentation and Consistency-Based Semi-Supervised Learning ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
On Graph Neural Networks versus Graph-Augmented MLPs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization ✅ ❌ ❌ ✅ ❌ ❌ ✅ 3
On Learning Universal Representations Across Languages ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
On Position Embeddings in BERT ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
On Self-Supervised Image Representations for GAN Evaluation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
On Statistical Bias In Active Learning: How and When to Fix It ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
On the Bottleneck of Graph Neural Networks and its Practical Implications ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On the Critical Role of Conventions in Adaptive Human-AI Collaboration ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
On the Dynamics of Training Attention Models ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
On the Impossibility of Global Convergence in Multi-Loss Optimization ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
On the Origin of Implicit Regularization in Stochastic Gradient Descent ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers ❌ ❌ ✅ ❌ ❌ ✅ ✅ 3
On the Transfer of Disentangled Representations in Realistic Settings ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
On the Universality of Rotation Equivariant Point Cloud Networks ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
On the Universality of the Double Descent Peak in Ridgeless Regression ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
On the geometry of generalization and memorization in deep neural networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On the mapping between Hopfield networks and Restricted Boltzmann Machines ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
On the role of planning in model-based deep reinforcement learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Online Adversarial Purification based on Self-supervised Learning ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Open Question Answering over Tables and Text ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Optimal Regularization can Mitigate Double Descent ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Optimism in Reinforcement Learning with Generalized Linear Function Approximation ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Orthogonalizing Convolutional Layers with the Cayley Transform ✅ ✅ ✅ ❌ ✅ ✅ ✅ 6
Overfitting for Fun and Profit: Instance-Adaptive Data Compression ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Overparameterisation and worst-case generalisation: friend or foe? ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
PAC Confidence Predictions for Deep Neural Network Classifiers ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds ❌ ❌ ✅ ✅ ❌ ❌ ❌ 2
PDE-Driven Spatiotemporal Disentanglement ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
PMI-Masking: Principled masking of correlated spans ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Parameter Efficient Multimodal Transformers for Video Representation Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Parameter-Based Value Functions ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Partitioned Learned Bloom Filters ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Personalized Federated Learning with First Order Model Optimization ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Physics-aware, probabilistic model order reduction with guaranteed stability ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Planning from Pixels using Inverse Dynamics Models ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics ✅ ✅ ❌ ❌ ✅ ❌ ✅ 4
PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Practical Real Time Recurrent Learning with a Sparse Approximation ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Pre-training Text-to-Text Transformers for Concept-centric Common Sense ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Predicting Classification Accuracy When Adding New Unobserved Classes ✅ ✅ ✅ ✅ ❌ ✅ ✅ 6
Predicting Inductive Biases of Pre-Trained Models ❌ ✅ ❌ ✅ ❌ ❌ ✅ 3
Predicting Infectiousness for Proactive Contact Tracing ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Prediction and generalisation over directed actions by grid cells ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Primal Wasserstein Imitation Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Private Image Reconstruction from System Side Channels Using Generative Models ❌ ✅ ✅ ❌ ✅ ✅ ✅ 5
Private Post-GAN Boosting ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Probabilistic Numeric Convolutional Neural Networks ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Probing BERT in Hyperbolic Spaces ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Progressive Skeletonization: Trimming more fat from a network at initialization ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Property Controllable Variational Autoencoder via Invertible Mutual Dependence ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Protecting DNNs from Theft using an Ensemble of Diverse Models ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Prototypical Contrastive Learning of Unsupervised Representations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Prototypical Representation Learning for Relation Extraction ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Provable Rich Observation Reinforcement Learning with Combinatorial Latent States ✅ ✅ ❌ ✅ ❌ ✅ ✅ 5
Provably robust classification of adversarial examples with detection ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Pruning Neural Networks at Initialization: Why Are We Missing the Mark? ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
QPLEX: Duplex Dueling Multi-Agent Q-Learning ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Quantifying Differences in Reward Functions ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
R-GAP: Recursive Gradient Attack on Privacy ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
RMSprop converges with proper hyper-parameter ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
RODE: Learning Roles to Decompose Multi-Agent Tasks ❌ ❌ ✅ ❌ ✅ ❌ ✅ 3
Random Feature Attention ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Randomized Automatic Differentiation ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Randomized Ensembled Double Q-Learning: Learning Fast Without a Model ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Rapid Task-Solving in Novel Environments ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Recurrent Independent Mechanisms ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Refining Deep Generative Models via Discriminator Gradient Flow ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Regularized Inverse Reinforcement Learning ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Reinforcement Learning with Random Delays ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Removing Undesirable Feature Contributions Using Out-of-Distribution Data ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Representation Balancing Offline Model-based Reinforcement Learning ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Representation Learning via Invariant Causal Mechanisms ❌ ❌ ✅ ❌ ❌ ❌ ❌ 1
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Representing Partial Programs with Blended Abstract Semantics ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
ResNet After All: Neural ODEs and Their Numerical Solution ✅ ✅ ✅ ❌ ❌ ✅ ✅ 5
Reset-Free Lifelong Learning with Skill-Space Planning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Rethinking Architecture Selection in Differentiable NAS ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Rethinking Attention with Performers ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Rethinking Embedding Coupling in Pre-trained Language Models ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Rethinking Positional Encoding in Language Pre-training ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Rethinking Soft Labels for Knowledge Distillation: A Bias–Variance Tradeoff Perspective ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Retrieval-Augmented Generation for Code Summarization via Hybrid GNN ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Return-Based Contrastive Representation Learning for Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Revisiting Dynamic Convolution via Matrix Decomposition ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Revisiting Few-sample BERT Fine-tuning ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Revisiting Locally Supervised Learning: an Alternative to End-to-end Training ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Ringing ReLUs: Harmonic Distortion Analysis of Nonlinear Feedforward Networks ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Risk-Averse Offline Reinforcement Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Robust Curriculum Learning: from clean label detection to noisy label self-correction ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
Robust Overfitting may be mitigated by properly learned smoothening ❌ ✅ ✅ ✅ ❌ ✅ ✅ 5
Robust Pruning at Initialization ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Robust and Generalizable Visual Representation Learning via Random Convolutions ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Robust early-learning: Hindering the memorization of noisy labels ✅ ✅ ✅ ✅ ✅ ✅ ✅ 7
SAFENet: A Secure, Accurate and Fast Neural Network Inference ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
SALD: Sign Agnostic Learning with Derivatives ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
SEDONA: Search for Decoupled Neural Networks toward Greedy Block-wise Learning ✅ ❌ ✅ ✅ ✅ ✅ ✅ 6
SEED: Self-supervised Distillation For Visual Representation ✅ ❌ ✅ ✅ ❌ ✅ ✅ 5
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
SOLAR: Sparse Orthogonal Learned and Random Embeddings ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
SSD: A Unified Framework for Self-Supervised Outlier Detection ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Saliency is a Possible Red Herring When Diagnosing Poor Generalization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Sample-Efficient Automated Deep Reinforcement Learning ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Scalable Bayesian Inverse Reinforcement Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Scalable Transfer Learning with Expert Models ❌ ❌ ✅ ✅ ✅ ❌ ❌ 3
Scaling Symbolic Methods using Gradients for Neural Model Explanation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Scaling the Convex Barrier with Active Sets ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Score-Based Generative Modeling through Stochastic Differential Equations ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Selective Classification Can Magnify Disparities Across Groups ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Self-Supervised Learning of Compressed Video Representations ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Self-Supervised Policy Adaptation during Deployment ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Self-supervised Adversarial Robustness for the Low-label, High-data Regime ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Self-supervised Learning from a Multi-view Perspective ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Self-supervised Representation Learning with Relative Predictive Coding ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Self-supervised Visual Reinforcement Learning with Object-centric Representations ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Self-training For Few-shot Transfer Across Extreme Task Differences ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Semantic Re-tuning with Contrastive Tension ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Semi-supervised Keypoint Localization ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Separation and Concentration in Deep Networks ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Set Prediction without Imposing Structure as Conditional Density Estimation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Shape or Texture: Understanding Discriminative Features in CNNs ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Shape-Texture Debiased Neural Network Training ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Shapley Explanation Networks ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Shapley explainability on the data manifold ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Sharpness-aware Minimization for Efficiently Improving Generalization ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU ❌ ✅ ❌ ❌ ✅ ✅ ❌ 3
Simple Augmentation Goes a Long Way: ADRL for DNN Quantization ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Simple Spectral Graph Convolution ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Single-Photon Image Classification ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
SkipW: Resource Adaptable RNN with Strict Upper Computational Limit ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Sliced Kernelized Stein Discrepancy ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Solving Compositional Reinforcement Learning Problems via Task Reduction ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Sparse Quantized Spectral Clustering ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Spatially Structured Recurrent Modules ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Spatio-Temporal Graph Scattering Transform ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Stabilized Medical Image Attacks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Statistical inference for individual fairness ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Structured Prediction as Translation between Augmented Natural Languages ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Support-set bottlenecks for video-text representation learning ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Symmetry-Aware Actor-Critic for 3D Molecular Design ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Systematic generalisation with group invariant predictions ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
Taking Notes on the Fly Helps Language Pre-Training ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Taming GANs with Lookahead-Minmax ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Task-Agnostic Morphology Evolution ✅ ✅ ❌ ❌ ❌ ❌ ✅ 3
Teaching Temporal Logics to Neural Networks ❌ ❌ ❌ ✅ ✅ ❌ ✅ 3
Teaching with Commentaries ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Temporally-Extended ε-Greedy Exploration ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Tent: Fully Test-Time Adaptation by Entropy Minimization ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Text Generation by Learning from Demonstrations ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
The Importance of Pessimism in Fixed-Dataset Policy Optimization ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
The Intrinsic Dimension of Images and Its Impact on Learning ❌ ✅ ✅ ❌ ❌ ❌ ❌ 2
The Recurrent Neural Tangent Kernel ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
The Risks of Invariant Risk Minimization ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
The geometry of integration in text classification RNNs ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
The inductive bias of ReLU networks on orthogonally separable data ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
The role of Disentanglement in Generalisation ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Theoretical bounds on estimation error for meta-learning ❌ ✅ ❌ ❌ ❌ ❌ ✅ 2
Tilted Empirical Risk Minimization ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
Topology-Aware Segmentation Using Discrete Morse Theory ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Towards Impartial Multi-task Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Towards Robust Neural Networks via Close-loop Control ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Towards Robustness Against Natural Language Word Substitutions ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Tradeoffs in Data Augmentation: An Empirical Study ❌ ❌ ✅ ✅ ❌ ✅ ✅ 4
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Training GANs with Stronger Augmentations via Contrastive Discriminator ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Training independent subnetworks for robust prediction ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Training with Quantization Noise for Extreme Model Compression ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Trajectory Prediction using Equivariant Continuous Convolution ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Transformer protein language models are unsupervised structure learners ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Transient Non-stationarity and Generalisation in Deep Reinforcement Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
TropEx: An Algorithm for Extracting Linear Terms in Deep Neural Networks ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Trusted Multi-View Classification ✅ ❌ ✅ ✅ ❌ ❌ ✅ 4
UMEC: Unified model and embedding compression for efficient recommendation systems ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Unbiased Teacher for Semi-Supervised Object Detection ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Uncertainty Estimation in Autoregressive Structured Prediction ❌ ❌ ✅ ✅ ✅ ❌ ✅ 4
Uncertainty Sets for Image Classifiers using Conformal Prediction ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Uncertainty in Gradient Boosting via Ensembles ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Uncertainty-aware Active Learning for Optimal Bayesian Classifier ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Understanding Over-parameterization in Generative Adversarial Networks ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Understanding and Improving Lexical Choice in Non-Autoregressive Translation ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Understanding the effects of data parallelism and sparsity on neural network training ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Understanding the failure modes of out-of-distribution generalization ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Understanding the role of importance weighting for deep learning ❌ ❌ ❌ ❌ ❌ ❌ ✅ 1
Undistillable: Making A Nasty Teacher That CANNOT teach students ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Universal approximation power of deep residual neural networks via nonlinear control theory ❌ ❌ ❌ ❌ ❌ ❌ ❌ 0
Unlearnable Examples: Making Personal Data Unexploitable ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
Unsupervised Audiovisual Synthesis via Exemplar Autoencoders ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
Unsupervised Discovery of 3D Physical Objects from Video ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Unsupervised Object Keypoint Learning using Local Spatial Predictability ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Usable Information and Evolution of Optimal Representations During Training ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Using latent space regression to analyze and leverage compositionality in GANs ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
VA-RED$^2$: Video Adaptive Redundancy Reduction ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models ❌ ❌ ✅ ❌ ✅ ✅ ✅ 4
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
VTNet: Visual Transformer Network for Object Goal Navigation ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
Variational Information Bottleneck for Effective Low-Resource Fine-Tuning ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Variational Intrinsic Control Revisited ✅ ❌ ❌ ❌ ❌ ❌ ✅ 2
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF ❌ ❌ ✅ ✅ ✅ ✅ ✅ 5
Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images ❌ ✅ ✅ ❌ ✅ ❌ ✅ 4
Viewmaker Networks: Learning Views for Unsupervised Representation Learning ✅ ✅ ✅ ✅ ❌ ❌ ✅ 5
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
WaNet - Imperceptible Warping-based Backdoor Attack ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Wandering within a world: Online contextualized few-shot learning ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Wasserstein Embedding for Graph Learning ❌ ✅ ✅ ✅ ✅ ✅ ✅ 6
Wasserstein-2 Generative Networks ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
WaveGrad: Estimating Gradients for Waveform Generation ✅ ❌ ✅ ✅ ✅ ❌ ✅ 5
What Can You Learn From Your Muscles? Learning Visual Representation from Human Interactions ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
What Makes Instance Discrimination Good for Transfer Learning? ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study ❌ ✅ ✅ ❌ ❌ ✅ ✅ 4
What Should Not Be Contrastive in Contrastive Learning ❌ ❌ ✅ ✅ ❌ ❌ ✅ 3
What are the Statistical Limits of Offline RL with Linear Function Approximation? ✅ ❌ ❌ ❌ ❌ ❌ ❌ 1
What they do when in doubt: a study of inductive biases in seq2seq learners ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3
When Do Curricula Work? ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
When Optimizing $f$-Divergence is Robust with Label Noise ✅ ✅ ✅ ❌ ❌ ❌ ✅ 4
When does preconditioning help or hurt generalization? ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets? ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients ❌ ❌ ✅ ❌ ❌ ❌ ✅ 2
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic ❌ ✅ ✅ ✅ ❌ ❌ ✅ 4
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching ✅ ✅ ✅ ✅ ✅ ❌ ✅ 6
WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic ✅ ❌ ✅ ❌ ✅ ❌ ✅ 4
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
You Only Need Adversarial Supervision for Semantic Image Synthesis ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Zero-Cost Proxies for Lightweight NAS ❌ ✅ ✅ ✅ ✅ ❌ ✅ 5
Zero-shot Synthesis with Group-Supervised Learning ✅ ❌ ✅ ❌ ❌ ❌ ✅ 3
gradSim: Differentiable simulation for system identification and visuomotor control ✅ ✅ ✅ ❌ ✅ ❌ ✅ 5
not-MIWAE: Deep Generative Modelling with Missing not at Random Data ❌ ✅ ✅ ❌ ❌ ❌ ✅ 3