Here are all the papers accepted to ICLR 2020. For this post, I used the data collected by shaohua0116/ICLR2020-OpenReviewData.

For just reinforcement learning papers, check this post.

Rank Average Rating Title Ratings Variance Decision
1 8.00 Optimal Strategies Against Generative Attacks 8 8 8 8 0.00 Accept (Talk)
1 8.00 Sparse Coding With Gated Learned Ista 8 8 8 0.00 Accept (Spotlight)
1 8.00 Dynamics-aware Unsupervised Skill Discovery 8 8 8 0.00 Accept (Talk)
1 8.00 Cater: A Diagnostic Dataset For Compositional Actions & Temporal Reasoning 8 8 8 0.00 Accept (Talk)
1 8.00 Learning To Balance: Bayesian Meta-learning For Imbalanced And Out-of-distribution Tasks 8 8 8 0.00 Accept (Talk)
1 8.00 A Generalized Training Approach For Multiagent Learning 8 8 8 0.00 Accept (Talk)
1 8.00 Contrastive Learning Of Structured World Models 8 8 8 0.00 Accept (Talk)
1 8.00 Enhancing Adversarial Defense By K-winners-take-all 8 8 8 0.00 Accept (Spotlight)
1 8.00 Backpack: Packing More Into Backprop 8 8 8 0.00 Accept (Talk)
1 8.00 Principled Weight Initialization For Hypernetworks 8 8 8 0.00 Accept (Talk)
1 8.00 Understanding And Robustifying Differentiable Architecture Search 8 8 8 0.00 Accept (Talk)
1 8.00 Restricting The Flow: Information Bottlenecks For Attribution 8 8 8 0.00 Accept (Talk)
1 8.00 Implementation Matters In Deep Rl: A Case Study On Ppo And Trpo 8 8 8 0.00 Accept (Talk)
1 8.00 Nas-bench-102: Extending The Scope Of Reproducible Neural Architecture Search 8 8 8 0.00 Accept (Spotlight)
1 8.00 Mathematical Reasoning In Latent Space 8 8 8 0.00 Accept (Talk)
1 8.00 Mirror-generative Neural Machine Translation 8 8 8 0.00 Accept (Talk)
1 8.00 Rotation-invariant Clustering Of Functional Cell Types In Primary Visual Cortex 8 8 8 0.00 Accept (Talk)
1 8.00 On The “steerability” Of Generative Adversarial Networks 8 8 8 0.00 Accept (Poster)
1 8.00 The Logical Expressiveness Of Graph Neural Networks 8 8 8 0.00 Accept (Spotlight)
1 8.00 Meta-learning With Warped Gradient Descent 8 8 8 0.00 Accept (Talk)
1 8.00 Differentiable Reasoning Over A Virtual Knowledge Base 8 8 8 0.00 Accept (Talk)
1 8.00 Differentiation Of Blackbox Combinatorial Solvers 8 8 8 0.00 Accept (Spotlight)
1 8.00 Geometric Analysis Of Nonconvex Optimization Landscapes For Overcomplete Learning 8 8 8 0.00 Accept (Talk)
1 8.00 Simplified Action Decoder For Deep Multi-agent Reinforcement Learning 8 8 8 0.00 Accept (Spotlight)
1 8.00 Gendice: Generalized Offline Estimation Of Stationary Values 8 8 8 0.00 Accept (Talk)
1 8.00 Data-dependent Gaussian Prior Objective For Language Generation 8 8 8 0.00 Accept (Talk)
1 8.00 Causal Discovery With Reinforcement Learning 8 8 8 0.00 Accept (Talk)
1 8.00 How Much Position Information Do Convolutional Neural Networks Encode? 8 8 8 0.00 Accept (Spotlight)
1 8.00 Why Gradient Clipping Accelerates Training: A Theoretical Justification For Adaptivity 8 8 8 0.00 Accept (Talk)
1 8.00 A Theory Of Usable Information Under Computational Constraints 8 8 0.00 Accept (Talk)
1 8.00 Freelb: Enhanced Adversarial Training For Language Understanding 8 8 0.00 Accept (Spotlight)
1 8.00 Hyper-sagnn: A Self-attention Based Graph Neural Network For Hypergraphs 8 8 0.00 Accept (Poster)
1 8.00 Smooth Markets: A Basic Mechanism For Organizing Gradient-based Learners 8 8 0.00 Accept (Poster)
1 8.00 Depth-width Trade-offs For Relu Networks Via Sharkovsky’s Theorem 8 8 0.00 Accept (Spotlight)
2 7.50 Vq-wav2vec: Self-supervised Learning Of Discrete Speech Representations 8 6 8 8 0.75 Accept (Poster)
2 7.50 Rna Secondary Structure Prediction By Learning Unrolled Algorithms 8 8 8 6 0.75 Accept (Talk)
3 7.33 Is A Good Representation Sufficient For Sample Efficient Reinforcement Learning? 8 8 6 0.89 Accept (Spotlight)
3 7.33 Adversarial Training And Provable Defenses: Bridging The Gap 8 6 8 0.89 Accept (Talk)
3 7.33 Low-resource Knowledge-grounded Dialogue Generation 6 8 8 0.89 Accept (Poster)
3 7.33 Truth Or Backpropaganda? An Empirical Investigation Of Deep Learning Theory 8 6 8 0.89 Accept (Spotlight)
3 7.33 Directional Message Passing For Molecular Graphs 6 8 8 0.89 Accept (Spotlight)
3 7.33 Reformer: The Efficient Transformer 8 8 6 0.89 Accept (Talk)
3 7.33 Cross-lingual Alignment Vs Joint Training: A Comparative Study And A Simple Unified Framework 6 8 8 0.89 Accept (Poster)
3 7.33 What Graph Neural Networks Cannot Learn: Depth Vs Width 8 6 8 0.89 Accept (Poster)
3 7.33 Assemblenet: Searching For Multi-stream Neural Connectivity In Video Architectures 6 8 8 0.89 Accept (Poster)
3 7.33 Compressive Transformers For Long-range Sequence Modelling 6 8 8 0.89 Accept (Poster)
3 7.33 At Stability’s Edge: How To Adjust Hyperparameters To Preserve Minima Selection In Asynchronous Training Of Neural Networks? 8 6 8 0.89 Accept (Spotlight)
3 7.33 Comparing Fine-tuning And Rewinding In Neural Network Pruning 8 6 8 0.89 Accept (Talk)
3 7.33 Mogrifier Lstm 6 8 8 0.89 Accept (Talk)
3 7.33 Graphzoom: A Multi-level Spectral Approach For Accurate And Scalable Graph Embedding 8 8 6 0.89 Accept (Talk)
3 7.33 Reconstructing Continuous Distributions Of 3d Protein Structure From Cryo-em Images 6 8 8 0.89 Accept (Spotlight)
3 7.33 Neural Network Branching For Neural Network Verification 8 6 8 0.89 Accept (Talk)
3 7.33 Online And Stochastic Optimization Beyond Lipschitz Continuity: A Riemannian Approach 8 8 6 0.89 Accept (Spotlight)
3 7.33 Polylogarithmic Width Suffices For Gradient Descent To Achieve Arbitrarily Small Test Error With Shallow Relu Networks 8 6 8 0.89 Accept (Poster)
3 7.33 Deep Network Classification By Scattering And Homotopy Dictionary Learning 8 8 6 0.89 Accept (Poster)
3 7.33 Meta-learning Without Memorization 8 6 8 0.89 Accept (Spotlight)
3 7.33 Harnessing Structures For Value-based Planning And Reinforcement Learning 6 8 8 0.89 Accept (Talk)
3 7.33 Unbiased Contrastive Divergence Algorithm For Training Energy-based Latent Variable Models 6 8 8 0.89 Accept (Spotlight)
3 7.33 Explain Your Move: Understanding Agent Actions Using Focused Feature Saliency 6 8 8 0.89 Accept (Poster)
3 7.33 Disentangling Neural Mechanisms For Perceptual Grouping 6 8 8 0.89 Accept (Spotlight)
3 7.33 Mixed-curvature Variational Autoencoders 6 8 8 0.89 Accept (Poster)
3 7.33 Symplectic Ode-net: Learning Hamiltonian Dynamics With Control 6 8 8 0.89 Accept (Poster)
3 7.33 Deep Batch Active Learning By Diverse, Uncertain Gradient Lower Bounds 8 6 8 0.89 Accept (Talk)
3 7.33 Deep Imitative Models For Flexible Inference, Planning, And Control 8 6 8 0.89 Accept (Poster)
3 7.33 Cyclical Stochastic Gradient Mcmc For Bayesian Deep Learning 6 8 8 0.89 Accept (Talk)
3 7.33 Scaling Autoregressive Video Models 6 8 8 0.89 Accept (Spotlight)
3 7.33 Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps 8 8 6 0.89 Accept (Spotlight)
3 7.33 A Mutual Information Maximization Perspective Of Language Representation Learning 6 8 8 0.89 Accept (Spotlight)
3 7.33 Ddsp: Differentiable Digital Signal Processing 8 6 8 0.89 Accept (Spotlight)
3 7.33 On Mutual Information Maximization For Representation Learning 8 8 6 0.89 Accept (Poster)
3 7.33 Observational Overfitting In Reinforcement Learning 6 8 8 0.89 Accept (Poster)
3 7.33 Federated Learning With Matched Averaging 6 8 8 0.89 Accept (Talk)
3 7.33 Latent Normalizing Flows For Many-to-many Cross Domain Mappings 6 8 8 0.89 Accept (Poster)
3 7.33 Convolutional Conditional Neural Processes 6 8 8 0.89 Accept (Talk)
3 7.33 Meta-q-learning 8 8 6 0.89 Accept (Talk)
3 7.33 Measuring The Reliability Of Reinforcement Learning Algorithms 8 8 6 0.89 Accept (Spotlight)
3 7.33 Physics-aware Difference Graph Networks For Sparsely-observed Dynamics 8 8 6 0.89 Accept (Poster)
3 7.33 Learning Hierarchical Discrete Linguistic Units From Visually-grounded Speech 6 8 8 0.89 Accept (Talk)
3 7.33 Symplectic Recurrent Neural Networks 8 8 6 0.89 Accept (Spotlight)
3 7.33 End To End Trainable Active Contours Via Differentiable Rendering 8 8 6 0.89 Accept (Poster)
3 7.33 What Can Neural Networks Reason About? 8 6 8 0.89 Accept (Spotlight)
3 7.33 Discriminative Particle Filter Reinforcement Learning For Complex Partial Observations 8 6 8 0.89 Accept (Poster)
3 7.33 Thieves On Sesame Street! Model Extraction Of Bert-based Apis 6 8 8 0.89 Accept (Poster)
3 7.33 High Fidelity Speech Synthesis With Adversarial Networks 8 6 8 0.89 Accept (Talk)
3 7.33 Disagreement-regularized Imitation Learning 6 8 8 0.89 Accept (Spotlight)
3 7.33 Stable Rank Normalization For Improved Generalization In Neural Networks And Gans 6 8 8 0.89 Accept (Spotlight)
3 7.33 Doubly Robust Bias Reduction In Infinite Horizon Off-policy Estimation 6 8 8 0.89 Accept (Spotlight)
3 7.33 Fasterseg: Searching For Faster Real-time Semantic Segmentation 6 8 8 0.89 Accept (Poster)
3 7.33 Robust Subspace Recovery Layer For Unsupervised Anomaly Detection 6 8 8 0.89 Accept (Poster)
3 7.33 Seed Rl: Scalable And Efficient Deep-rl With Accelerated Central Inference 8 6 8 0.89 Accept (Talk)
3 7.33 On The Equivalence Between Node Embeddings And Structural Graph Representations 6 8 8 0.89 Accept (Poster)
3 7.33 Harnessing The Power Of Infinitely Wide Deep Nets On Small-data Tasks 8 6 8 0.89 Accept (Spotlight)
3 7.33 The Ingredients Of Real World Robotic Reinforcement Learning 6 8 8 0.89 Accept (Spotlight)
3 7.33 Watch The Unobserved: A Simple Approach To Parallelizing Monte Carlo Tree Search 8 6 8 0.89 Accept (Talk)
3 7.33 Meta-learning Acquisition Functions For Transfer Learning In Bayesian Optimization 8 6 8 0.89 Accept (Spotlight)
3 7.33 On The Convergence Of Fedavg On Non-iid Data 6 8 8 0.89 Accept (Talk)
3 7.33 Classification-based Anomaly Detection For General Data 8 8 6 0.89 Accept (Poster)
3 7.33 Learning Robust Representations Via Multi-view Information Bottleneck 6 8 8 0.89 Accept (Poster)
3 7.33 Poly-encoders: Architectures And Pre-training Strategies For Fast And Accurate Multi-sentence Scoring 8 6 8 0.89 Accept (Poster)
3 7.33 Your Classifier Is Secretly An Energy Based Model And You Should Treat It Like One 6 8 8 0.89 Accept (Talk)
3 7.33 Deep Learning For Symbolic Mathematics 8 8 6 0.89 Accept (Spotlight)
3 7.33 Progressive Learning And Disentanglement Of Hierarchical Representations 6 8 8 0.89 Accept (Spotlight)
3 7.33 Energy-based Models For Atomic-resolution Protein Conformations 6 8 8 0.89 Accept (Spotlight)
3 7.33 Lambdanet: Probabilistic Type Inference Using Graph Neural Networks 6 8 8 0.89 Accept (Poster)
3 7.33 Sumo: Unbiased Estimation Of Log Marginal Probability For Latent Variable Models 6 8 8 0.89 Accept (Spotlight)
3 7.33 Glad: Learning Sparse Graph Recovery 8 6 8 0.89 Accept (Poster)
3 7.33 Program Guided Agent 8 6 8 0.89 Accept (Spotlight)
3 7.33 Graph Neural Networks Exponentially Lose Expressive Power For Node Classification 8 6 8 0.89 Accept (Spotlight)
3 7.33 A Closer Look At Deep Policy Gradients 8 6 8 0.89 Accept (Talk)
3 7.33 Fast Task Inference With Variational Intrinsic Successor Features 8 6 8 0.89 Accept (Talk)
3 7.33 Generalization Of Two-layer Neural Networks: An Asymptotic Viewpoint 8 6 8 0.89 Accept (Spotlight)
3 7.33 Electra: Pre-training Text Encoders As Discriminators Rather Than Generators 8 8 6 0.89 Accept (Poster)
3 7.33 Network Deconvolution 6 8 8 0.89 Accept (Spotlight)
3 7.33 Intensity-free Learning Of Temporal Point Processes 8 6 8 0.89 Accept (Spotlight)
3 7.33 Fspool: Learning Set Representations With Featurewise Sort Pooling 8 8 6 0.89 Accept (Poster)
3 7.33 Massively Multilingual Sparse Word Representations 6 8 8 0.89 Accept (Poster)
3 7.33 Finite Depth And Width Corrections To The Neural Tangent Kernel 6 8 8 0.89 Accept (Spotlight)
3 7.33 Gradient Descent Maximizes The Margin Of Homogeneous Neural Networks 8 8 6 0.89 Accept (Talk)
3 7.33 Sequential Latent Knowledge Selection For Knowledge-grounded Dialogue 8 8 6 0.89 Accept (Spotlight)
3 7.33 Learning To Plan In High Dimensions Via Neural Exploration-exploitation Trees 8 8 6 0.89 Accept (Spotlight)
3 7.33 Albert: A Lite Bert For Self-supervised Learning Of Language Representations 8 8 6 0.89 Accept (Spotlight)
4 7.00 An Exponential Learning Rate Schedule For Batch Normalized Networks 8 8 6 6 1.00 Accept (Spotlight)
4 7.00 Encoding Word Order In Complex Embeddings 8 6 8 6 1.00 Accept (Spotlight)
4 7.00 And The Bit Goes Down: Revisiting The Quantization Of Neural Networks 8 6 8 6 1.00 Accept (Spotlight)
4 7.00 Quantum Algorithms For Deep Convolutional Neural Networks 6 8 8 6 1.00 Accept (Poster)
4 7.00 Target-embedding Autoencoders For Supervised Representation Learning 6 8 6 8 1.00 Accept (Talk)
4 7.00 Dream To Control: Learning Behaviors By Latent Imagination 8 6 6 8 1.00 Accept (Spotlight)
4 7.00 Memo: A Deep Network For Flexible Combination Of Episodic Memories 6 8 1.00 Accept (Poster)
4 7.00 Explanation By Progressive Exaggeration 6 8 1.00 Accept (Spotlight)
4 7.00 Ridge Regression: Structure, Cross-validation, And Sketching 6 8 1.00 Accept (Spotlight)
4 7.00 Double Neural Counterfactual Regret Minimization 8 6 1.00 Accept (Poster)
4 7.00 Biologically Inspired Sleep Algorithm For Increased Generalization And Adversarial Robustness In Deep Neural Networks 6 8 1.00 Accept (Poster)
4 7.00 Spectral Embedding Of Regularized Block Models 8 6 1.00 Accept (Spotlight)
4 7.00 How The Choice Of Activation Affects Training Of Overparametrized Neural Nets 6 8 1.00 Accept (Poster)
4 7.00 Understanding L4-based Dictionary Learning: Interpretation, Stability, And Robustness 8 6 1.00 Accept (Poster)
4 7.00 Neural Tangent Kernels, Transportation Mappings, And Universal Approximation 8 6 1.00 Accept (Poster)
4 7.00 Sliced Cramer Synaptic Consolidation For Preserving Deeply Learned Representations 6 8 1.00 Accept (Spotlight)
4 7.00 Language Gans Falling Short 6 8 1.00 Accept (Poster)
4 7.00 Building Deep Equivariant Capsule Networks 8 6 1.00 Accept (Talk)
5 6.75 An Inductive Bias For Distances: Neural Nets That Respect The Triangle Inequality 8 8 3 8 4.69 Accept (Poster)
6 6.67 Disentanglement Through Nonlinear Ica With General Incompressible-flow Networks (gin) 8 6 6 0.89 Accept (Spotlight)
6 6.67 Fooling Detection Alone Is Not Enough: Adversarial Attack Against Multiple Object Tracking 8 6 6 0.89 Accept (Poster)
6 6.67 In Search For A Sat-friendly Binarized Neural Network Architecture 8 6 6 0.89 Accept (Poster)
6 6.67 Dba: Distributed Backdoor Attacks Against Federated Learning 6 8 6 0.89 Accept (Poster)
6 6.67 Genesis: Generative Scene Inference And Sampling With Object-centric Latent Representations 6 6 8 0.89 Accept (Poster)
6 6.67 Measuring Compositional Generalization: A Comprehensive Method On Realistic Data 6 8 6 0.89 Accept (Poster)
6 6.67 Lagrangian Fluid Simulation With Continuous Convolutions 6 8 6 0.89 Accept (Poster)
6 6.67 Making Efficient Use Of Demonstrations To Solve Hard Exploration Problems 6 8 6 0.89 Accept (Poster)
6 6.67 Intrinsic Motivation For Encouraging Synergistic Behavior 6 8 6 0.89 Accept (Poster)
6 6.67 On Robustness Of Neural Ordinary Differential Equations 6 8 6 0.89 Accept (Spotlight)
6 6.67 On Identifiability In Transformers 6 8 6 0.89 Accept (Poster)
6 6.67 Estimating Gradients For Discrete Random Variables By Sampling Without Replacement 6 6 8 0.89 Accept (Spotlight)
6 6.67 Gradient-based Neural Dag Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Incremental Rnn: A Dynamical View. 8 6 6 0.89 Accept (Poster)
6 6.67 Deep Double Descent: Where Bigger Models And More Data Hurt 8 6 6 0.89 Accept (Poster)
6 6.67 Learning To Retrieve Reasoning Paths Over Wikipedia Graph For Question Answering 6 6 8 0.89 Accept (Poster)
6 6.67 Simple And Effective Regularization Methods For Training On Noisily Labeled Data With Generalization Guarantee 6 8 6 0.89 Accept (Poster)
6 6.67 Sqil: Imitation Learning Via Reinforcement Learning With Sparse Rewards 8 6 6 0.89 Accept (Poster)
6 6.67 Reinforcement Learning With Competitive Ensembles Of Information-constrained Primitives 8 6 6 0.89 Accept (Poster)
6 6.67 Neural Outlier Rejection For Self-supervised Keypoint Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Rényi Fair Inference 6 6 8 0.89 Accept (Poster)
6 6.67 U-gat-it: Unsupervised Generative Attentional Networks With Adaptive Layer-instance Normalization For Image-to-image Translation 6 8 6 0.89 Accept (Poster)
6 6.67 Multi-agent Interactions Modeling With Correlated Policies 6 6 8 0.89 Accept (Poster)
6 6.67 Decoupling Representation And Classifier For Long-tailed Recognition 6 8 6 0.89 Accept (Poster)
6 6.67 Estimating Counterfactual Treatment Outcomes Over Time Through Adversarially Balanced Representations 8 6 6 0.89 Accept (Spotlight)
6 6.67 Neural Symbolic Reader: Scalable Integration Of Distributed And Symbolic Representations For Reading Comprehension 6 6 8 0.89 Accept (Spotlight)
6 6.67 Inductive Representation Learning On Temporal Graphs 6 6 8 0.89 Accept (Poster)
6 6.67 Training Generative Adversarial Networks From Incomplete Observations Using Factorised Discriminators 6 8 6 0.89 Accept (Poster)
6 6.67 Denoising And Regularization Via Exploiting The Structural Bias Of Convolutional Generators 6 8 6 0.89 Accept (Poster)
6 6.67 Controlling Generative Models With Continuous Factors Of Variations 6 8 6 0.89 Accept (Poster)
6 6.67 Intrinsically Motivated Discovery Of Diverse Patterns In Self-organizing Systems 6 6 8 0.89 Accept (Talk)
6 6.67 Influence-based Multi-agent Exploration 6 6 8 0.89 Accept (Spotlight)
6 6.67 Asymptotics Of Wide Networks From Feynman Diagrams 8 6 6 0.89 Accept (Spotlight)
6 6.67 Provable Robustness Against All Adversarial -perturbations For 6 8 6 0.89 Accept (Poster)
6 6.67 From Variational To Deterministic Autoencoders 6 8 6 0.89 Accept (Poster)
6 6.67 A Probabilistic Formulation Of Unsupervised Text Style Transfer 8 6 6 0.89 Accept (Spotlight)
6 6.67 Black-box Adversarial Attack With Transferable Model-based Embedding 6 8 6 0.89 Accept (Poster)
6 6.67 Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree On The Truth 6 6 8 0.89 Accept (Poster)
6 6.67 Pitfalls Of In-domain Uncertainty Estimation And Ensembling In Deep Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Learning The Arrow Of Time For Problems In Reinforcement Learning 6 6 8 0.89 Accept (Poster)
6 6.67 Transformer-xh: Multi-hop Question Answering With Extra Hop Attention 6 8 6 0.89 Accept (Poster)
6 6.67 Learned Step Size Quantization 6 6 8 0.89 Accept (Poster)
6 6.67 Mutual Mean-teaching: Pseudo Label Refinery For Unsupervised Domain Adaptation On Person Re-identification 6 8 6 0.89 Accept (Poster)
6 6.67 Ensemble Distribution Distillation 6 6 8 0.89 Accept (Poster)
6 6.67 Drawing Early-bird Tickets: Toward More Efficient Training Of Deep Networks 8 6 6 0.89 Accept (Spotlight)
6 6.67 Detecting And Diagnosing Adversarial Images With Class-conditional Capsule Reconstructions 6 8 6 0.89 Accept (Poster)
6 6.67 Order Learning And Its Application To Age Estimation 6 6 8 0.89 Accept (Poster)
6 6.67 Inductive Matrix Completion Based On Graph Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Posterior Sampling For Multi-agent Reinforcement Learning: Solving Extensive Games With Imperfect Information 6 6 8 0.89 Accept (Talk)
6 6.67 Intriguing Properties Of Adversarial Training At Scale 6 8 6 0.89 Accept (Poster)
6 6.67 Efficient Transformer For Mobile Applications 6 8 6 0.89 Accept (Poster)
6 6.67 Reducing Transformer Depth On Demand With Structured Dropout 6 6 8 0.89 Accept (Poster)
6 6.67 A Theoretical Analysis Of The Number Of Shots In Few-shot Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Learning Representations For Binary-classification Without Backpropagation 8 6 6 0.89 Accept (Poster)
6 6.67 Fsnet: Compression Of Deep Convolutional Neural Networks By Filter Summary 8 6 6 0.89 Accept (Poster)
6 6.67 Amrl: Aggregated Memory For Reinforcement Learning 6 6 8 0.89 Accept (Poster)
6 6.67 The Function Of Contextual Illusions 6 6 8 0.89 Accept (Poster)
6 6.67 Neural Machine Translation With Universal Visual Representation 6 8 6 0.89 Accept (Spotlight)
6 6.67 Information Geometry Of Orthogonal Initializations And Training 6 8 6 0.89 Accept (Poster)
6 6.67 Batch-shaping For Learning Conditional Channel Gated Networks 6 6 8 0.89 Accept (Poster)
6 6.67 Multi-scale Representation Learning For Spatial Feature Distributions Using Grid Cells 6 8 6 0.89 Accept (Spotlight)
6 6.67 Query-efficient Meta Attack To Deep Neural Networks 6 8 6 0.89 Accept (Poster)
6 6.67 A Fair Comparison Of Graph Neural Networks For Graph Classification 6 8 6 0.89 Accept (Poster)
6 6.67 Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates 6 8 6 0.89 Accept (Poster)
6 6.67 Monotonic Multihead Attention 6 8 6 0.89 Accept (Poster)
6 6.67 Continual Learning With Hypernetworks 6 8 6 0.89 Accept (Poster)
6 6.67 Decoding As Dynamic Programming For Recurrent Autoregressive Models 6 6 8 0.89 Accept (Poster)
6 6.67 Diverse Trajectory Forecasting With Determinantal Point Processes 8 6 6 0.89 Accept (Poster)
6 6.67 Co-attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-occurring In Data 6 8 6 0.89 Accept (Poster)
6 6.67 Multiplicative Interactions And Where To Find Them 6 8 6 0.89 Accept (Poster)
6 6.67 You Can Teach An Old Dog New Tricks! On Training Knowledge Graph Embeddings 8 6 6 0.89 Accept (Poster)
6 6.67 Deepsphere: A Graph-based Spherical Cnn 8 6 6 0.89 Accept (Spotlight)
6 6.67 Learning To Control Pdes With Differentiable Physics 6 8 6 0.89 Accept (Spotlight)
6 6.67 Emergence Of Functional And Structural Properties Of The Head Direction System By Optimization Of Recurrent Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Model Based Reinforcement Learning For Atari 6 8 6 0.89 Accept (Spotlight)
6 6.67 Dynamically Pruned Message Passing Networks For Large-scale Knowledge Graph Reasoning 6 8 6 0.89 Accept (Poster)
6 6.67 Mixout: Effective Regularization To Finetune Large-scale Pretrained Language Models 6 8 6 0.89 Accept (Poster)
6 6.67 On The Geometry And Learning Low-dimensional Embeddings For Directed Graphs 6 6 8 0.89 Accept (Poster)
6 6.67 The Break-even Point On The Optimization Trajectories Of Deep Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Understanding And Improving Information Transfer In Multi-task Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Abductive Commonsense Reasoning 6 8 6 0.89 Accept (Poster)
6 6.67 Tree-structured Attention With Hierarchical Accumulation 6 6 8 0.89 Accept (Poster)
6 6.67 Pay Attention To Features, Transfer Learn Faster Cnns 8 6 6 0.89 Accept (Poster)
6 6.67 Gradientless Descent: High-dimensional Zeroth-order Optimization 6 8 6 0.89 Accept (Spotlight)
6 6.67 Knowledge Consistency Between Neural Networks And Beyond 6 8 6 0.89 Accept (Poster)
6 6.67 Learning From Rules Generalizing Labeled Exemplars 6 8 6 0.89 Accept (Spotlight)
6 6.67 Variational Recurrent Models For Solving Partially Observable Control Tasks 6 6 8 0.89 Accept (Poster)
6 6.67 Towards Hierarchical Importance Attribution: Explaining Compositional Semantics For Neural Sequence Models 6 6 8 0.89 Accept (Spotlight)
6 6.67 Tranquil Clouds: Neural Networks For Learning Temporally Coherent Features In Point Clouds 6 8 6 0.89 Accept (Spotlight)
6 6.67 Spike-based Causal Inference For Weight Alignment 8 6 6 0.89 Accept (Poster)
6 6.67 Sample Efficient Policy Gradient Methods With Recursive Variance Reduction 6 8 6 0.89 Accept (Poster)
6 6.67 Exploring Model-based Planning With Policy Networks 6 8 6 0.89 Accept (Poster)
6 6.67 Variational Autoencoders For Highly Multivariate Spatial Point Processes Intensities 6 8 6 0.89 Accept (Poster)
6 6.67 Kernelized Wasserstein Natural Gradient 6 8 6 0.89 Accept (Spotlight)
6 6.67 Can Gradient Clipping Mitigate Label Noise? 6 6 8 0.89 Accept (Poster)
6 6.67 Rethinking The Security Of Skip Connections In Resnet-like Neural Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Reinforcement Learning Based Graph-to-sequence Model For Natural Question Generation 6 6 8 0.89 Accept (Poster)
6 6.67 Deep Neuroethology Of A Virtual Rodent 6 6 8 0.89 Accept (Spotlight)
6 6.67 Pretrained Encyclopedia: Weakly Supervised Knowledge-pretrained Language Model 6 6 8 0.89 Accept (Poster)
6 6.67 N-beats: Neural Basis Expansion Analysis For Interpretable Time Series Forecasting 6 6 8 0.89 Accept (Poster)
6 6.67 Uncertainty-guided Continual Learning With Bayesian Neural Networks 8 6 6 0.89 Accept (Poster)
6 6.67 Toward Amortized Ranking-critical Training For Collaborative Filtering 6 6 8 0.89 Accept (Poster)
6 6.67 Revisiting Self-training For Neural Sequence Generation 6 6 8 0.89 Accept (Poster)
6 6.67 A Neural Dirichlet Process Mixture Model For Task-free Continual Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Ride: Rewarding Impact-driven Exploration For Procedurally-generated Environments 6 6 8 0.89 Accept (Poster)
6 6.67 Neurquri: Neural Question Requirement Inspector For Answerability Prediction In Machine Reading Comprehension 6 6 8 0.89 Accept (Poster)
6 6.67 Actor-critic Provably Finds Nash Equilibria Of Linear-quadratic Mean-field Games 6 6 8 0.89 Accept (Poster)
6 6.67 Lipschitz Constant Estimation For Neural Networks Via Sparse Polynomial Optimization 6 8 6 0.89 Accept (Poster)
6 6.67 A Latent Morphology Model For Open-vocabulary Neural Machine Translation 8 6 6 0.89 Accept (Spotlight)
6 6.67 Are Pre-trained Language Models Aware Of Phrases? Simple But Strong Baselines For Grammar Induction 6 6 8 0.89 Accept (Poster)
6 6.67 Padé Activation Units: End-to-end Learning Of Flexible Activation Functions In Deep Networks 6 8 6 0.89 Accept (Poster)
6 6.67 Improving Adversarial Robustness Requires Revisiting Misclassified Examples 8 6 6 0.89 Accept (Poster)
6 6.67 Learning Expensive Coordination: An Event-based Deep Rl Approach 6 8 6 0.89 Accept (Poster)
6 6.67 Scalable Model Compression By Entropy Penalized Reparameterization 6 8 6 0.89 Accept (Poster)
6 6.67 Permutation Equivariant Models For Compositional Generalization In Language 8 6 6 0.89 Accept (Poster)
6 6.67 Evolutionary Population Curriculum For Scaling Multi-agent Reinforcement Learning 6 8 6 0.89 Accept (Poster)
6 6.67 On The Interaction Between Supervision And Self-play In Emergent Communication 6 8 6 0.89 Accept (Poster)
6 6.67 Locality And Compositionality In Zero-shot Learning 8 6 6 0.89 Accept (Poster)
6 6.67 Distributed Bandit Learning: Near-optimal Regret With Efficient Communication 8 6 6 0.89 Accept (Poster)
6 6.67 Fast Is Better Than Free: Revisiting Adversarial Training 8 6 6 0.89 Accept (Poster)
6 6.67 Towards Stabilizing Batch Statistics In Backward Propagation Of Batch Normalization 6 8 6 0.89 Accept (Poster)
6 6.67 Extreme Tensoring For Low-memory Preconditioning 8 6 6 0.89 Accept (Poster)
6 6.67 Scale-equivariant Steerable Networks 6 6 8 0.89 Accept (Poster)
6 6.67 Query2box: Reasoning Over Knowledge Graphs In Vector Space Using Box Embeddings 6 6 8 0.89 Accept (Poster)
6 6.67 Consistency Regularization For Generative Adversarial Networks 8 6 6 0.89 Accept (Poster)
6 6.67 Making Sense Of Reinforcement Learning And Probabilistic Inference 6 6 8 0.89 Accept (Spotlight)
6 6.67 Reclor: A Reading Comprehension Dataset Requiring Logical Reasoning 6 6 8 0.89 Accept (Poster)
6 6.67 Semi-supervised Generative Modeling For Controllable Speech Synthesis 6 8 6 0.89 Accept (Poster)
6 6.67 Reinforced Genetic Algorithm Learning For Optimizing Computation Graphs 8 6 6 0.89 Accept (Poster)
6 6.67 The Intriguing Role Of Module Criticality In The Generalization Of Deep Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Training Individually Fair Ml Models With Sensitive Subspace Robustness 8 6 6 0.89 Accept (Spotlight)
6 6.67 Tabfact: A Large-scale Dataset For Table-based Fact Verification 8 6 6 0.89 Accept (Poster)
6 6.67 Snode: Spectral Discretization Of Neural Odes For System Identification 6 6 8 0.89 Accept (Poster)
6 6.67 Clevrer: Collision Events For Video Representation And Reasoning 6 8 6 0.89 Accept (Spotlight)
6 6.67 Never Give Up: Learning Directed Exploration Strategies 6 6 8 0.89 Accept (Poster)
6 6.67 Robust Reinforcement Learning For Continuous Control With Model Misspecification 6 6 8 0.89 Accept (Poster)
6 6.67 Neural Module Networks For Reasoning Over Text 6 8 6 0.89 Accept (Poster)
6 6.67 Sign Bits Are All You Need For Black-box Attacks 8 6 6 0.89 Accept (Poster)
6 6.67 Learning To Learn By Zeroth-order Oracle 6 8 6 0.89 Accept (Poster)
6 6.67 Synthesizing Programmatic Policies That Inductively Generalize 6 8 6 0.89 Accept (Poster)
6 6.67 Hamiltonian Generative Networks 8 6 6 0.89 Accept (Spotlight)
6 6.67 Prediction, Consistency, Curvature: Representation Learning For Locally-linear Control 6 8 6 0.89 Accept (Poster)
6 6.67 A Function Space View Of Bounded Norm Infinite Width Relu Nets: The Multivariate Case 6 6 8 0.89 Accept (Poster)
6 6.67 Hilloc: Lossless Image Compression With Hierarchical Latent Variable Models 6 6 8 0.89 Accept (Poster)
6 6.67 Geom-gcn: Geometric Graph Convolutional Networks 6 8 6 0.89 Accept (Spotlight)
6 6.67 Adaptive Correlated Monte Carlo For Contextual Categorical Sequence Generation 6 6 8 0.89 Accept (Poster)
6 6.67 Pc-darts: Partial Channel Connections For Memory-efficient Architecture Search 6 6 8 0.89 Accept (Spotlight)
6 6.67 Improving Generalization In Meta Reinforcement Learning Using Neural Objectives 6 6 8 0.89 Accept (Spotlight)
6 6.67 Compression Based Bound For Non-compressed Network: Unified Generalization Error Analysis Of Large Compressible Deep Neural Network 6 8 6 0.89 Accept (Spotlight)
6 6.67 Hoppity: Learning Graph Transformations To Detect And Fix Bugs In Programs 6 8 6 0.89 Accept (Spotlight)
6 6.67 Real Or Not Real, That Is The Question 8 6 6 0.89 Accept (Spotlight)
7 6.50 A Closer Look At The Approximation Capabilities Of Neural Networks 8 6 6 6 0.75 Accept (Poster)
7 6.50 Quantifying Point-prediction Uncertainty In Neural Networks Via Residual Estimation With An I/o Kernel 6 6 8 6 0.75 Accept (Poster)
7 6.50 Learning Compositional Koopman Operators For Model-based Control 6 6 6 8 0.75 Accept (Spotlight)
7 6.50 Learning To Guide Random Search 8 6 6 6 0.75 Accept (Poster)
7 6.50 Dynamic Time Lag Regression: Predicting What & When 8 6 6 6 0.75 Accept (Poster)
7 6.50 Deepv2d: Video To Depth With Differentiable Structure From Motion 6 6 6 8 0.75 Accept (Poster)
7 6.50 Rethinking Softmax Cross-entropy Loss For Adversarial Robustness 8 6 6 6 0.75 Accept (Poster)
8 6.33 Understanding Knowledge Distillation In Non-autoregressive Machine Translation 8 3 8 5.56 Accept (Poster)
8 6.33 Self-labelling Via Simultaneous Clustering And Representation Learning 8 3 8 5.56 Accept (Spotlight)
8 6.33 Self-adversarial Learning With Comparative Discrimination For Text Generation 3 8 8 5.56 Accept (Poster)
8 6.33 Defending Against Physically Realizable Attacks On Image Classification 3 8 8 5.56 Accept (Spotlight)
8 6.33 Lazy-cfr: Fast And Near-optimal Regret Minimization For Extensive Games With Imperfect Information 3 8 8 5.56 Accept (Poster)
8 6.33 Variational Template Machine For Data-to-text Generation 8 3 8 5.56 Accept (Poster)
8 6.33 Word2ket: Space-efficient Word Embeddings Inspired By Quantum Entanglement 3 8 8 5.56 Accept (Spotlight)
8 6.33 Rapid Learning Or Feature Reuse? Towards Understanding The Effectiveness Of Maml 8 3 8 5.56 Accept (Poster)
8 6.33 Learning Disentangled Representations For Counterfactual Regression 8 8 3 5.56 Accept (Poster)
8 6.33 Accelerating Sgd With Momentum For Over-parameterized Learning 8 8 3 5.56 Accept (Poster)
8 6.33 A Meta-transfer Objective For Learning To Disentangle Causal Mechanisms 3 8 8 5.56 Accept (Poster)
8 6.33 Learning From Explanations With Neural Module Execution Tree 3 8 8 5.56 Accept (Poster)
8 6.33 Fantastic Generalization Measures And Where To Find Them 8 3 8 5.56 Accept (Poster)
8 6.33 Guiding Program Synthesis By Learning To Generate Examples 8 3 8 5.56 Accept (Poster)
8 6.33 Single Episode Transfer For Differing Environmental Dynamics In Reinforcement Learning 3 8 8 5.56 Accept (Poster)
8 6.33 Triple Wins: Boosting Accuracy, Robustness And Efficiency Together By Enabling Input-adaptive Inference 3 8 8 5.56 Accept (Poster)
8 6.33 Coherent Gradients: An Approach To Understanding Generalization In Gradient Descent-based Optimization 8 8 3 5.56 Accept (Poster)
8 6.33 Learning-augmented Data Stream Algorithms 3 8 8 5.56 Accept (Poster)
8 6.33 Weakly Supervised Disentanglement With Guarantees 8 8 3 5.56 Accept (Poster)
8 6.33 Transferable Perturbations Of Deep Feature Distributions 8 3 8 5.56 Accept (Poster)
8 6.33 Measuring And Improving The Use Of Graph Information In Graph Neural Networks 8 3 8 5.56 Accept (Poster)
8 6.33 Automated Relational Meta-learning 3 8 8 5.56 Accept (Poster)
8 6.33 Minimizing Flops To Learn Efficient Sparse Representations 8 3 8 5.56 Accept (Poster)
8 6.33 Snow: Subscribing To Knowledge Via Channel Pooling For Transfer & Lifelong Learning 8 8 3 5.56 Accept (Poster)
8 6.33 Decentralized Distributed Ppo: Mastering Pointgoal Navigation 3 8 8 5.56 Accept (Poster)
8 6.33 Augmix: A Simple Data Processing Method To Improve Robustness And Uncertainty 8 3 8 5.56 Accept (Poster)
8 6.33 Counterfactuals Uncover The Modular Structure Of Deep Generative Models 8 3 8 5.56 Accept (Poster)
9 6.25 Improved Sample Complexities For Deep Neural Networks And Robust Classification Via An All-layer Margin 6 8 8 3 4.19 Accept (Poster)
9 6.25 Geometric Insights Into The Convergence Of Nonlinear Td Learning 8 3 6 8 4.19 Accept (Poster)
9 6.25 Dynamics-aware Embeddings 3 8 6 8 4.19 Accept (Poster)
10 6.20 Reanalysis Of Variance Reduced Temporal Difference Learning 8 8 6 3 6 3.36 Accept (Poster)
11 6.00 Meta-learning Deep Energy-based Memory Models 6 6 6 6 0.00 Accept (Poster)
11 6.00 Memory-based Graph Networks 6 6 6 6 0.00 Accept (Poster)
11 6.00 Training Binary Neural Networks With Real-to-binary Convolutions 6 6 6 6 0.00 Accept (Poster)
11 6.00 Lookahead: A Far-sighted Alternative Of Magnitude-based Pruning 6 6 6 6 0.00 Accept (Poster)
11 6.00 Q-learning With Ucb Exploration Is Sample Efficient For Infinite-horizon Mdp 6 6 6 6 0.00 Accept (Poster)
11 6.00 On The Variance Of The Adaptive Learning Rate And Beyond 6 6 6 0.00 Accept (Poster)
11 6.00 Emergent Systematic Generalization In A Situated Agent 6 6 6 0.00 Accept (Poster)
11 6.00 Quantifying The Cost Of Reliable Photo Authentication Via High-performance Learned Lossy Representations 6 6 6 0.00 Accept (Poster)
11 6.00 Automated Curriculum Generation Through Setter-solver Interactions 6 6 6 0.00 Accept (Poster)
11 6.00 Optimistic Exploration Even With A Pessimistic Initialisation 6 6 6 0.00 Accept (Poster)
11 6.00 Multi-agent Reinforcement Learning For Networked System Control 6 6 6 0.00 Accept (Poster)
11 6.00 Physics-as-inverse-graphics: Unsupervised Physical Parameter Estimation From Video 6 6 6 0.00 Accept (Poster)
11 6.00 On Solving Minimax Optimization Locally: A Follow-the-ridge Approach 6 6 6 0.00 Accept (Poster)
11 6.00 A Learning-based Iterative Method For Solving Vehicle Routing Problems 6 6 6 0.00 Accept (Poster)
11 6.00 Deephoyer: Learning Sparser Neural Network With Differentiable Scale-invariant Sparsity Measures 6 6 6 0.00 Accept (Poster)
11 6.00 Probabilistic Connection Importance Inference And Lossless Compression Of Deep Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Precision Gating: Improving Neural Network Efficiency With Dynamic Dual-precision Activations 6 6 6 0.00 Accept (Poster)
11 6.00 Learning To Link 6 6 6 0.00 Accept (Poster)
11 6.00 Remixmatch: Semi-supervised Learning With Distribution Matching And Augmentation Anchoring 6 6 6 0.00 Accept (Poster)
11 6.00 Differentially Private Meta-learning 6 6 6 0.00 Accept (Poster)
11 6.00 Fast Neural Network Adaptation Via Parameters Remapping 6 6 6 0.00 Accept (Poster)
11 6.00 Sharing Knowledge In Multi-task Deep Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Rtfm: Generalising To New Environment Dynamics Via Reading 6 6 6 0.00 Accept (Poster)
11 6.00 Strategies For Pre-training Graph Neural Networks 6 6 6 0.00 Accept (Spotlight)
11 6.00 Adversarial Lipschitz Regularization 6 6 6 0.00 Accept (Poster)
11 6.00 Meta Reinforcement Learning With Autonomous Inference Of Subtask Dependencies 6 6 6 0.00 Accept (Poster)
11 6.00 Deformable Kernels: Adapting Effective Receptive Fields For Object Deformation 6 6 6 0.00 Accept (Poster)
11 6.00 Incorporating Bert Into Neural Machine Translation 6 6 6 0.00 Accept (Poster)
11 6.00 Distance-based Learning From Errors For Confidence Calibration 6 6 6 0.00 Accept (Poster)
11 6.00 Dividemix: Learning With Noisy Labels As Semi-supervised Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Projection Based Constrained Policy Optimization 6 6 6 0.00 Accept (Poster)
11 6.00 Adversarial Policies: Attacking Deep Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 One-shot Pruning Of Recurrent Neural Networks By Jacobian Spectrum Evaluation 6 6 6 0.00 Accept (Poster)
11 6.00 Sampling-free Learning Of Bayesian Quantized Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Understanding Generalization In Recurrent Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Graph Constrained Reinforcement Learning For Natural Language Action Spaces 6 6 6 0.00 Accept (Poster)
11 6.00 Spikegrad: An Ann-equivalent Computation Model For Implementing Backpropagation With Spikes 6 6 6 0.00 Accept (Poster)
11 6.00 Extracting And Leveraging Feature Interaction Interpretations 6 6 6 0.00 Accept (Poster)
11 6.00 Gradient Regularization For Quantization Robustness 6 6 6 0.00 Accept (Poster)
11 6.00 Masked Based Unsupervised Content Transfer 6 6 6 0.00 Accept (Poster)
11 6.00 A Framework For Robustness Certification Of Smoothed Classifiers Using F-divergences 6 6 6 0.00 Accept (Poster)
11 6.00 V-mpo: On-policy Maximum A Posteriori Policy Optimization For Discrete And Continuous Control 6 6 6 0.00 Accept (Poster)
11 6.00 Mixed Precision Dnns: All You Need Is A Good Parametrization 6 6 6 0.00 Accept (Poster)
11 6.00 Thinking While Moving: Deep Reinforcement Learning With Concurrent Control 6 6 6 0.00 Accept (Poster)
11 6.00 Don’t Use Large Mini-batches, Use Local Sgd 6 6 6 0.00 Accept (Poster)
11 6.00 Keep Doing What Worked: Behavior Modelling Priors For Offline Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Imitation Learning Via Off-policy Distribution Matching 6 6 6 0.00 Accept (Poster)
11 6.00 Empirical Bayes Transductive Meta-learning With Synthetic Gradients 6 6 6 0.00 Accept (Poster)
11 6.00 On The Relationship Between Self-attention And Convolutional Layers 6 6 6 0.00 Accept (Poster)
11 6.00 A Closer Look At The Optimization Landscapes Of Generative Adversarial Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Unsupervised Clustering Using Pseudo-semi-supervised Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Adversarial Autoaugment 6 6 6 0.00 Accept (Poster)
11 6.00 Dynamic Model Pruning With Feedback 6 6 6 0.00 Accept (Poster)
11 6.00 Understanding The Limitations Of Variational Mutual Information Estimators 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Semi-supervised Anomaly Detection 6 6 6 0.00 Accept (Poster)
11 6.00 Graph Convolutional Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Understanding The Limitations Of Conditional Generative Models 6 6 6 0.00 Accept (Poster)
11 6.00 Scalable Neural Methods For Reasoning With A Symbolic Knowledge Base 6 6 6 0.00 Accept (Poster)
11 6.00 Graphaf: A Flow-based Autoregressive Model For Molecular Graph Generation 6 6 6 0.00 Accept (Poster)
11 6.00 Evaluating The Search Phase Of Neural Architecture Search 6 6 6 0.00 Accept (Poster)
11 6.00 Adversarial Example Detection And Classification With Asymmetrical Adversarial Training 6 6 6 0.00 Accept (Poster)
11 6.00 Adaptive Structural Fingerprints For Graph Attention Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality 6 6 6 0.00 Accept (Poster)
11 6.00 On Universal Equivariant Set Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Option Discovery Using Deep Skill Chaining 6 6 6 0.00 Accept (Poster)
11 6.00 Unpaired Point Cloud Completion On Real Scans Using Adversarial Training 6 6 6 0.00 Accept (Poster)
11 6.00 Jelly Bean World: A Testbed For Never-ending Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Probabilistic Subsampling For Task-adaptive Compressed Sensing 6 6 6 0.00 Accept (Poster)
11 6.00 Residual Energy-based Models For Text Generation 6 6 6 0.00 Accept (Poster)
11 6.00 State-only Imitation With Transition Dynamics Mismatch 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Graph Matching Consensus 6 6 6 0.00 Accept (Poster)
11 6.00 Unsupervised Model Selection For Variational Disentangled Representation Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Slomo: Improving Communication-efficient Distributed Sgd With Slow Momentum 6 6 6 0.00 Accept (Poster)
11 6.00 Learning Self-correctable Policies And Value Functions From Demonstrations With Negative Sampling 6 6 6 0.00 Accept (Poster)
11 6.00 Cophy: Counterfactual Learning Of Physical Dynamics 6 6 6 0.00 Accept (Spotlight)
11 6.00 The Gambler’s Problem And Beyond 6 6 6 0.00 Accept (Poster)
11 6.00 Structured Object-aware Physics Prediction For Video Modeling And Planning 6 6 6 0.00 Accept (Poster)
11 6.00 Combining Q-learning And Search With Amortized Value Estimates 6 6 6 0.00 Accept (Poster)
11 6.00 Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints 6 6 6 0.00 Accept (Poster)
11 6.00 Robust And Interpretable Blind Image Denoising Via Bias-free Convolutional Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Vid2game: Controllable Characters Extracted From Real-world Videos 6 6 6 0.00 Accept (Poster)
11 6.00 Infinite-horizon Differentiable Model Predictive Control 6 6 6 0.00 Accept (Poster)
11 6.00 Advectivenet: An Eulerian-lagrangian Fluidic Reservoir For Point Cloud Processing 6 6 6 0.00 Accept (Poster)
11 6.00 Once For All: Train One Network And Specialize It For Efficient Deployment 6 6 6 0.00 Accept (Poster)
11 6.00 Graph Inference Learning For Semi-supervised Classification 6 6 6 0.00 Accept (Poster)
11 6.00 Theory And Evaluation Metrics For Learning Disentangled Representations 6 6 6 0.00 Accept (Poster)
11 6.00 The Implicit Bias Of Depth: How Incremental Learning Drives Generalization 6 6 6 0.00 Accept (Poster)
11 6.00 A Stochastic Derivative Free Optimization Method With Momentum 6 6 6 0.00 Accept (Poster)
11 6.00 Stochastic Auc Maximization With Deep Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Metapix: Few-shot Video Retargeting 6 6 6 0.00 Accept (Poster)
11 6.00 Videoflow: A Conditional Flow-based Model For Stochastic Video Generation 6 6 6 0.00 Accept (Poster)
11 6.00 Scalable Object-oriented Sequential Generative Models 6 6 6 0.00 Accept (Poster)
11 6.00 Mixup Inference: Better Exploiting Mixup To Defend Adversarial Attacks 6 6 6 0.00 Accept (Poster)
11 6.00 Conservative Uncertainty Estimation By Fitting Prior Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Rapp: Novelty Detection With Reconstruction Along Projection Pathway 6 6 6 0.00 Accept (Poster)
11 6.00 Novelty Detection Via Blurring 6 6 6 0.00 Accept (Poster)
11 6.00 Detecting Extrapolation With Local Ensembles 6 6 6 0.00 Accept (Poster)
11 6.00 Learning To Solve The Credit Assignment Problem 6 6 6 0.00 Accept (Poster)
11 6.00 Pac Confidence Sets For Deep Neural Networks Via Calibrated Prediction 6 6 6 0.00 Accept (Poster)
11 6.00 Dynamical Distance Learning For Semi-supervised And Unsupervised Skill Discovery 6 6 6 0.00 Accept (Poster)
11 6.00 The Local Elasticity Of Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Infograph: Unsupervised And Semi-supervised Graph-level Representation Learning Via Mutual Information Maximization 6 6 6 0.00 Accept (Spotlight)
11 6.00 Are Transformers Universal Approximators Of Sequence-to-sequence Functions? 6 6 6 0.00 Accept (Poster)
11 6.00 Stochastic Conditional Generative Networks With Basis Decomposition 6 6 6 0.00 Accept (Poster)
11 6.00 Attributes Obfuscation With Complex-valued Features 6 6 6 0.00 Accept (Poster)
11 6.00 Composition-based Multi-relational Graph Convolutional Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Structpool: Structured Graph Pooling Via Conditional Random Fields 6 6 6 0.00 Accept (Poster)
11 6.00 On Generalization Error Bounds Of Noisy Gradient Methods For Non-convex Learning 6 6 6 0.00 Accept (Poster)
11 6.00 A Target-agnostic Attack On Deep Models: Exploiting Security Vulnerabilities Of Transfer Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Meta-learning Curiosity Algorithms 6 6 6 0.00 Accept (Poster)
11 6.00 On Computation And Generalization Of Gener- Ative Adversarial Imitation Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Unrestricted Adversarial Examples Via Semantic Manipulation 6 6 6 0.00 Accept (Poster)
11 6.00 Towards Neural Networks That Provably Know When They Don’t Know 6 6 6 0.00 Accept (Poster)
11 6.00 Exploration In Reinforcement Learning With Deep Covering Options 6 6 6 0.00 Accept (Poster)
11 6.00 A Baseline For Few-shot Image Classification 6 6 6 0.00 Accept (Poster)
11 6.00 Towards Fast Adaptation Of Neural Architectures With Meta Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Cross-domain Few-shot Classification Via Learned Feature-wise Transformation 6 6 6 0.00 Accept (Spotlight)
11 6.00 Learning To Move With Affordance Maps 6 6 6 0.00 Accept (Poster)
11 6.00 Cm3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 To Relieve Your Headache Of Training An Mrf, Take Advil 6 6 6 0.00 Accept (Poster)
11 6.00 Analysis Of Video Feature Learning In Two-stream Cnns On The Example Of Zebrafish Swim Bout Classification 6 6 6 0.00 Accept (Poster)
11 6.00 Beyond Linearization: On Quadratic And Higher-order Approximation Of Wide Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Conditional Learning Of Fair Representations 6 6 6 0.00 Accept (Spotlight)
11 6.00 Curvature Graph Network 6 6 6 0.00 Accept (Poster)
11 6.00 Pruned Graph Scattering Transforms 6 6 6 0.00 Accept (Poster)
11 6.00 The Curious Case Of Neural Text Degeneration 6 6 6 0.00 Accept (Poster)
11 6.00 Graphsaint: Graph Sampling Based Inductive Learning Method 6 6 6 0.00 Accept (Poster)
11 6.00 Learning To Coordinate Manipulation Skills Via Skill Behavior Diversification 6 6 6 0.00 Accept (Poster)
11 6.00 Expected Information Maximization: Using The I-projection For Mixture Density Estimation 6 6 6 0.00 Accept (Poster)
11 6.00 Generative Ratio Matching Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Composing Task-agnostic Policies With Deep Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Selection Via Proxy: Efficient Data Selection For Deep Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Frequency-based Search-control In Dyna 6 6 6 0.00 Accept (Poster)
11 6.00 Demystifying Inter-class Disentanglement 6 6 6 0.00 Accept (Poster)
11 6.00 Continual Learning With Bayesian Neural Networks For Non-stationary Data 6 6 6 0.00 Accept (Poster)
11 6.00 Inductive And Unsupervised Representation Learning On Graph Structured Objects 6 6 6 0.00 Accept (Poster)
11 6.00 Picking Winning Tickets Before Training By Preserving Gradient Flow 6 6 6 0.00 Accept (Poster)
11 6.00 Certified Defenses For Adversarial Patches 6 6 6 0.00 Accept (Poster)
11 6.00 Multilingual Alignment Of Contextual Word Representations 6 6 6 0.00 Accept (Poster)
11 6.00 Black-box Off-policy Estimation For Infinite-horizon Reinforcement Learning 6 6 6 0.00 Accept (Poster)
11 6.00 Compositional Languages Emerge In A Neural Iterated Learning Model 6 6 6 0.00 Accept (Poster)
11 6.00 Rethinking The Hyperparameters For Fine-tuning 6 6 6 0.00 Accept (Poster)
11 6.00 The Shape Of Data: Intrinsic Distance For Data Distributions 6 6 6 0.00 Accept (Poster)
11 6.00 On The Global Convergence Of Training Deep Linear Resnets 6 6 6 0.00 Accept (Poster)
11 6.00 Action Semantics Network: Considering The Effects Of Actions In Multiagent Systems 6 6 6 0.00 Accept (Poster)
11 6.00 Curriculum Loss: Robust Learning And Generalization Against Label Corruption 6 6 6 0.00 Accept (Poster)
11 6.00 Tensor Decompositions For Temporal Knowledge Base Completion 6 6 6 0.00 Accept (Poster)
11 6.00 Towards Better Understanding Of Adaptive Gradient Algorithms In Generative Adversarial Nets 6 6 6 0.00 Accept (Poster)
11 6.00 Why Not To Use Zero Imputation? Correcting Sparsity Bias In Training Neural Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Enabling Deep Spiking Neural Networks With Hybrid Conversion And Spike Timing Dependent Backpropagation 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Audio Priors Emerge From Harmonic Convolutional Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Binaryduo: Reducing Gradient Mismatch In Binary Activation Network By Coupling Binary Activations 6 6 6 0.00 Accept (Poster)
11 6.00 Pseudo-lidar++: Accurate Depth For 3d Object Detection In Autonomous Driving 6 6 6 0.00 Accept (Poster)
11 6.00 Adjustable Real-time Style Transfer 6 6 6 0.00 Accept (Poster)
11 6.00 You Only Train Once: Loss-conditional Training Of Deep Networks 6 6 6 0.00 Accept (Poster)
11 6.00 Progressive Memory Banks For Incremental Domain Adaptation 6 6 6 0.00 Accept (Poster)
11 6.00 Certified Robustness For Top-k Predictions Against Adversarial Perturbations Via Randomized Smoothing 6 6 6 0.00 Accept (Poster)
11 6.00 Deep Orientation Uncertainty Learning Based On A Bingham Loss 6 6 0.00 Accept (Poster)
11 6.00 Caql: Continuous Action Q-learning 6 6 0.00 Accept (Poster)
11 6.00 Identifying Through Flows For Recovering Latent Representations 6 6 0.00 Accept (Poster)
11 6.00 Reinforced Active Learning For Image Segmentation 6 6 0.00 Accept (Poster)
11 6.00 Towards A Deep Network Architecture For Structured Smoothness 6 6 0.00 Accept (Poster)
11 6.00 The Variational Bandwidth Bottleneck: Stochastic Evaluation On An Information Budget 6 6 0.00 Accept (Poster)
11 6.00 Bounds On Over-parameterization For Guaranteed Existence Of Descent Paths In Shallow Relu Networks 6 6 0.00 Accept (Poster)
11 6.00 On Bonus Based Exploration Methods In The Arcade Learning Environment 6 6 0.00 Accept (Poster)
11 6.00 Hierarchical Foresight: Self-supervised Learning Of Long-horizon Tasks Via Visual Subgoal Generation 6 6 0.00 Accept (Poster)
12 5.75 Maximum Likelihood Constraint Inference For Inverse Reinforcement Learning 8 6 3 6 3.19 Accept (Spotlight)
12 5.75 Autoq: Automated Kernel-wise Neural Network Quantization 6 6 8 3 3.19 Accept (Poster)
12 5.75 Towards Verified Robustness Under Text Deletion Interventions 3 6 8 6 3.19 Accept (Poster)
12 5.75 Mutual Information Gradient Estimation For Representation Learning 6 3 6 8 3.19 Accept (Poster)
12 5.75 Computation Reallocation For Object Detection 8 6 6 3 3.19 Accept (Poster)
12 5.75 Learning The Difference That Makes A Difference With Counterfactually-augmented Data 8 6 1 8 8.19 Accept (Spotlight)
12 5.75 Varibad: A Very Good Method For Bayes-adaptive Deep Rl Via Meta-learning 8 6 8 1 8.19 Accept (Poster)
12 5.75 Pcmc-net: Feature-based Pairwise Choice Markov Chains 8 6 6 3 3.19 Accept (Poster)
12 5.75 Image-guided Neural Object Rendering 6 3 8 6 3.19 Accept (Poster)
12 5.75 Neural Arithmetic Units 8 3 6 6 3.19 Accept (Spotlight)
12 5.75 Es-maml: Simple Hessian-free Meta Learning 8 8 6 1 8.19 Accept (Poster)
12 5.75 Probability Calibration For Knowledge Graph Embedding Models 6 8 3 6 3.19 Accept (Poster)
12 5.75 Span Recovery For Deep Neural Networks With Applications To Input Obfuscation 3 6 8 6 3.19 Accept (Poster)
12 5.75 White Noise Analysis Of Neural Networks 6 6 8 3 3.19 Accept (Spotlight)
13 5.67 From Inference To Generation: End-to-end Fully Self-supervised Generation Of Human Face From Speech 8 3 6 4.22 Accept (Poster)
13 5.67 Variance Reduction With Sparse Gradients 8 6 3 4.22 Accept (Poster)
13 5.67 Large Batch Optimization For Deep Learning: Training Bert In 76 Minutes 6 8 3 4.22 Accept (Poster)
13 5.67 Robust Local Features For Improving The Generalization Of Adversarial Training 8 3 6 4.22 Accept (Poster)
13 5.67 Watch, Try, Learn: Meta-learning From Demonstrations And Rewards 8 3 6 4.22 Accept (Poster)
13 5.67 Editable Neural Networks 8 3 6 4.22 Accept (Poster)
13 5.67 Prediction Poisoning: Towards Defenses Against Dnn Model Stealing Attacks 3 8 6 4.22 Accept (Poster)
13 5.67 Population-guided Parallel Policy Search For Reinforcement Learning 6 8 3 4.22 Accept (Poster)
13 5.67 Nas Evaluation Is Frustratingly Hard 8 8 1 10.89 Accept (Poster)
13 5.67 Learning Execution Through Neural Code Fusion 3 8 6 4.22 Accept (Poster)
13 5.67 Neural Stored-program Memory 6 8 3 4.22 Accept (Poster)
13 5.67 A Simple Randomization Technique For Generalization In Deep Reinforcement Learning 8 3 6 4.22 Accept (Poster)
13 5.67 On The Weaknesses Of Reinforcement Learning For Neural Machine Translation 8 6 3 4.22 Accept (Poster)
13 5.67 Self: Learning To Filter Noisy Labels With Self-ensembling 3 8 6 4.22 Accept (Poster)
13 5.67 Provable Benefit Of Orthogonal Initialization In Optimizing Deep Linear Networks 6 3 8 4.22 Accept (Poster)
13 5.67 Emergent Tool Use From Multi-agent Autocurricula 3 8 6 4.22 Accept (Spotlight)
13 5.67 Sadam: A Variant Of Adam For Strongly Convex Functions 3 6 8 4.22 Accept (Poster)
13 5.67 Deep Learning Of Determinantal Point Processes Via Proper Spectral Sub-gradient 6 3 8 4.22 Accept (Poster)
13 5.67 Meta Dropout: Learning To Perturb Latent Features For Generalization 6 8 3 4.22 Accept (Poster)
13 5.67 Functional Vs. Parametric Equivalence Of Relu Networks 6 8 3 4.22 Accept (Poster)
13 5.67 Neural Policy Gradient Methods: Global Optimality And Rates Of Convergence 3 6 8 4.22 Accept (Poster)
13 5.67 State Alignment-based Imitation Learning 6 8 3 4.22 Accept (Poster)
13 5.67 Self-supervised Learning Of Appliance Usage 8 3 6 4.22 Accept (Poster)
13 5.67 Finding And Visualizing Weaknesses Of Deep Reinforcement Learning Agents 8 6 3 4.22 Accept (Poster)
13 5.67 Neural Oblivious Decision Ensembles For Deep Learning On Tabular Data 3 8 6 4.22 Accept (Poster)
13 5.67 Model-augmented Actor-critic: Backpropagating Through Paths 3 6 8 4.22 Accept (Poster)
13 5.67 Macer: Attack-free And Scalable Robust Training Via Maximizing Certified Radius 8 6 3 4.22 Accept (Poster)
13 5.67 Behaviour Suite For Reinforcement Learning 8 3 6 4.22 Accept (Spotlight)
13 5.67 Variational Hetero-encoder Randomized Gans For Joint Image-text Modeling 6 8 3 4.22 Accept (Poster)
13 5.67 Bertscore: Evaluating Text Generation With Bert 6 3 8 4.22 Accept (Poster)
13 5.67 Learning To Explore Using Active Neural Mapping 8 3 6 4.22 Accept (Poster)
13 5.67 Learning Transport Cost From Subset Correspondence 8 6 3 4.22 Accept (Poster)
13 5.67 Generative Models For Effective Ml On Private, Decentralized Datasets 8 6 3 4.22 Accept (Poster)
13 5.67 Empirical Studies On The Properties Of Linear Regions In Deep Neural Networks 8 6 3 4.22 Accept (Poster)
13 5.67 Meta-dataset: A Dataset Of Datasets For Learning To Learn From Few Examples 3 6 8 4.22 Accept (Poster)
13 5.67 Compositional Continual Language Learning 3 8 6 4.22 Accept (Poster)
13 5.67 Data-independent Neural Pruning Via Coresets 6 8 3 4.22 Accept (Poster)
13 5.67 Learning Heuristics For Quantified Boolean Formulas Through Reinforcement Learning 6 8 3 4.22 Accept (Poster)
13 5.67 Augmenting Genetic Algorithms With Deep Neural Networks For Exploring The Chemical Space 8 6 3 4.22 Accept (Poster)
13 5.67 A Signal Propagation Perspective For Pruning Neural Networks At Initialization 6 8 3 4.22 Accept (Spotlight)
13 5.67 Neural Tangents: Fast And Easy Infinite Neural Networks In Python 3 8 6 4.22 Accept (Spotlight)
13 5.67 Structbert: Incorporating Language Structures Into Pre-training For Deep Language Understanding 6 8 3 4.22 Accept (Poster)
13 5.67 Nas-bench-1shot1: Benchmarking And Dissecting One-shot Neural Architecture Search 8 8 1 10.89 Accept (Poster)
13 5.67 Adversarially Robust Representations With Smooth Encoders 8 3 6 4.22 Accept (Poster)
13 5.67 Iterative Energy-based Projection On A Normal Data Manifold For Anomaly Localization 8 6 3 4.22 Accept (Poster)
13 5.67 Bridging Mode Connectivity In Loss Landscapes And Adversarial Robustness 6 8 3 4.22 Accept (Poster)
13 5.67 Identity Crisis: Memorization And Generalization Under Extreme Overparameterization 8 3 6 4.22 Accept (Poster)
13 5.67 B-spline Cnns On Lie Groups 6 3 8 4.22 Accept (Poster)
13 5.67 Adversarially Robust Transfer Learning 1 8 8 10.89 Accept (Poster)
13 5.67 Improved Memory In Recurrent Neural Networks With Sequential Non-normal Dynamics 3 8 6 4.22 Accept (Poster)
13 5.67 Towards Stable And Efficient Training Of Verifiably Robust Neural Networks 8 3 6 4.22 Accept (Poster)
13 5.67 Transferring Optimality Across Data Distributions Via Homotopy Methods 6 8 3 4.22 Accept (Poster)
13 5.67 The Asymptotic Spectrum Of The Hessian Of Dnn Throughout Training 3 8 6 4.22 Accept (Poster)
13 5.67 Learn To Explain Efficiently Via Neural Logic Inductive Learning 3 6 8 4.22 Accept (Poster)
13 5.67 Robust Training With Ensemble Consensus 8 6 3 4.22 Accept (Poster)
13 5.67 Domain Adaptive Multiflow Networks 8 6 3 4.22 Accept (Poster)
13 5.67 Distributionally Robust Neural Networks 6 8 3 4.22 Accept (Poster)
13 5.67 Learning To Group: A Bottom-up Framework For 3d Part Discovery In Unseen Categories 3 6 8 4.22 Accept (Poster)
13 5.67 The Early Phase Of Neural Network Training 3 8 6 4.22 Accept (Poster)
13 5.67 Extreme Classification Via Adversarial Softmax Approximation 8 6 3 4.22 Accept (Poster)
13 5.67 Convergence Behaviour Of Some Gradient-based Methods On Bilinear Zero-sum Games 3 8 6 4.22 Accept (Poster)
13 5.67 Gradients As Features For Deep Representation Learning 8 3 6 4.22 Accept (Poster)
13 5.67 Capsules With Inverted Dot-product Attention Routing 3 8 6 4.22 Accept (Poster)
13 5.67 Implicit Bias Of Gradient Descent Based Adversarial Training On Separable Data 6 8 3 4.22 Accept (Poster)
13 5.67 Understanding Architectures Learnt By Cell-based Neural Architecture Search 8 6 3 4.22 Accept (Poster)
13 5.67 Maxmin Q-learning: Controlling The Estimation Bias Of Q-learning 8 6 3 4.22 Accept (Poster)
13 5.67 Kernel Of Cyclegan As A Principal Homogeneous Space 8 6 3 4.22 Accept (Poster)
13 5.67 Neural Execution Of Graph Algorithms 1 8 8 10.89 Accept (Poster)
13 5.67 On Need For Topology-aware Generative Models For Manifold-based Defenses 3 8 6 4.22 Accept (Poster)
13 5.67 Universal Approximation With Certified Networks 6 8 3 4.22 Accept (Poster)
13 5.67 Discovering Motor Programs By Recomposing Demonstrations 3 6 8 4.22 Accept (Poster)
13 5.67 Hypermodels For Exploration 8 3 6 4.22 Accept (Poster)
14 5.50 Sub-policy Adaptation For Hierarchical Reinforcement Learning 3 8 6.25 Accept (Poster)
14 5.50 Pairnorm: Tackling Oversmoothing In Gnns 3 8 6.25 Accept (Poster)
14 5.50 Svqn: Sequential Variational Soft Q-learning Networks 3 8 6.25 Accept (Poster)
14 5.50 Cln2inv: Learning Loop Invariants With Continuous Logic Networks 3 8 6.25 Accept (Poster)
15 5.25 Spatially Parallel Attention And Component Extraction For Scene Decomposition 6 6 3 6 1.69 Accept (Poster)
15 5.25 Impact: Importance Weighted Asynchronous Architectures With Clipped Target Networks 6 3 6 6 1.69 Accept (Poster)
15 5.25 Shifted And Squeezed 8-bit Floating Point Format For Low-precision Training Of Deep Neural Networks 6 8 1 6 6.69 Accept (Poster)
15 5.25 Visual Representation Learning With 3d View-constrastive Inverse Graphics Networks 3 6 6 6 1.69 Accept (Poster)
16 5.00 V4d: 4d Convonlutional Neural Networks For Video-level Representation Learning 3 6 6 2.00 Accept (Poster)
16 5.00 Ranking Policy Gradient 6 3 6 2.00 Accept (Poster)
16 5.00 Regularizing Activations In Neural Networks Via Distribution Matching With The Wassertein Metric 6 6 3 2.00 Accept (Poster)
16 5.00 Cross-lingual Ability Of Multilingual Bert: An Empirical Study 6 6 3 2.00 Accept (Poster)
16 5.00 Abstract Diagrammatic Reasoning With Multiplex Graph Networks 6 3 6 2.00 Accept (Poster)
16 5.00 Augmenting Non-collaborative Dialog Systems With Explicit Semantic And Strategic Dialog History 6 3 6 2.00 Accept (Poster)
16 5.00 Mma Training: Direct Input Space Margin Maximization Through Adversarial Training 6 6 3 2.00 Accept (Poster)
16 5.00 Generalized Convolutional Forest Networks For Domain Generalization And Visual Recognition 6 3 6 2.00 Accept (Poster)
16 5.00 Weakly Supervised Clustering By Exploiting Unique Class Count 8 1 6 8.67 Accept (Poster)
16 5.00 Additive Powers-of-two Quantization: A Non-uniform Discretization For Neural Networks 6 3 6 2.00 Accept (Poster)
16 5.00 Jacobian Adversarially Regularized Networks For Robustness 6 6 3 2.00 Accept (Poster)
16 5.00 Lamol: Language Modeling For Lifelong Language Learning 6 3 6 2.00 Accept (Poster)
16 5.00 Training Recurrent Neural Networks Online By Learning Explicit State Variables 3 6 6 2.00 Accept (Poster)
16 5.00 Relational State-space Model For Stochastic Multi-object Systems 3 6 6 2.00 Accept (Poster)
16 5.00 Stochastic Weight Averaging In Parallel: Large-batch Training That Generalizes Well 3 6 6 2.00 Accept (Poster)
16 5.00 Bayesian Meta Sampling For Fast Uncertainty Adaptation 3 6 6 2.00 Accept (Poster)
16 5.00 Phase Transitions For The Information Bottleneck In Representation Learning 6 3 6 2.00 Accept (Poster)
16 5.00 Neural Text Generation With Unlikelihood Training 3 6 6 2.00 Accept (Poster)
16 5.00 Model-based Reinforcement Learning For Biological Sequence Design 6 3 6 2.00 Accept (Poster)
16 5.00 Depth-adaptive Transformer 6 6 3 2.00 Accept (Poster)
16 5.00 Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers 3 6 6 2.00 Accept (Poster)
16 5.00 Critical Initialisation In Continuous Approximations Of Binary Neural Networks 6 6 3 2.00 Accept (Poster)
16 5.00 Prox-sgd: Training Structured Neural Networks Under Regularization And Constraints 6 6 3 2.00 Accept (Poster)
16 5.00 Bayesopt Adversarial Attack 6 6 3 2.00 Accept (Poster)
16 5.00 Chameleon: Adaptive Code Optimization For Expedited Deep Neural Network Compilation 3 6 6 2.00 Accept (Poster)
16 5.00 Learning Nearly Decomposable Value Functions Via Communication Minimization 6 6 3 2.00 Accept (Poster)
16 5.00 Difference-seeking Generative Adversarial Network–unseen Sample Generation 6 6 3 2.00 Accept (Poster)
16 5.00 Learning Deep Graph Matching With Channel-independent Embedding And Hungarian Attention 6 6 3 2.00 Accept (Poster)
16 5.00 Robust Anomaly Detection And Backdoor Attack Detection Via Differential Privacy 6 6 3 2.00 Accept (Poster)
16 5.00 Robustness Verification For Transformers 6 6 3 2.00 Accept (Poster)
16 5.00 Implementing Inductive Bias For Different Navigation Tasks Through Diverse Rnn Attrractors 3 6 6 2.00 Accept (Poster)
16 5.00 Enhancing Transformation-based Defenses Against Adversarial Attacks With A Distribution Classifier 6 3 6 2.00 Accept (Poster)
16 5.00 Functional Regularisation For Continual Learning With Gaussian Processes 6 6 3 2.00 Accept (Poster)
16 5.00 Toward Evaluating Robustness Of Deep Reinforcement Learning With Continuous Control 6 3 6 2.00 Accept (Poster)
16 5.00 Learning Efficient Parameter Server Synchronization Policies For Distributed Sgd 6 3 6 2.00 Accept (Poster)
16 5.00 Understanding Why Neural Networks Generalize Well Through Gsnr Of Parameters 6 3 6 2.00 Accept (Spotlight)
16 5.00 Smoothness And Stability In Gans 8 6 1 8.67 Accept (Poster)
16 5.00 Plug And Play Language Model: A Simple Baseline For Controlled Language Generation 6 3 6 2.00 Accept (Poster)
16 5.00 A Constructive Prediction Of The Generalization Error Across Scales 1 6 8 8.67 Accept (Poster)
16 5.00 Contrastive Representation Distillation 6 6 3 2.00 Accept (Poster)
16 5.00 Differentiable Learning Of Numerical Rules In Knowledge Graphs 6 6 3 2.00 Accept (Poster)
16 5.00 Infinite-horizon Off-policy Policy Evaluation With Multiple Behavior Policies 3 6 6 2.00 Accept (Poster)
16 5.00 Rgbd-gan: Unsupervised 3d Representation Learning From Natural Image Datasets Via Rgbd Image Synthesis 6 3 6 2.00 Accept (Poster)
16 5.00 Generalization Through Memorization: Nearest Neighbor Language Models 6 6 3 2.00 Accept (Poster)
16 5.00 Decentralized Deep Learning With Arbitrary Communication Compression 6 6 3 2.00 Accept (Poster)
16 5.00 Escaping Saddle Points Faster With Stochastic Momentum 6 3 6 2.00 Accept (Poster)
16 5.00 Linear Symmetric Quantization Of Neural Networks For Low-precision Integer Hardware 3 6 6 2.00 Accept (Poster)
16 5.00 Nesterov Accelerated Gradient And Scale Invariance For Adversarial Attacks 3 6 6 2.00 Accept (Poster)
16 5.00 Scalable And Order-robust Continual Learning With Additive Parameter Decomposition 8 1 6 8.67 Accept (Poster)
16 5.00 Four Things Everyone Should Know To Improve Batch Normalization 6 6 3 2.00 Accept (Poster)
16 5.00 Define: Deep Factorized Input Word Embeddings For Neural Sequence Modeling 6 3 6 2.00 Accept (Poster)
16 5.00 Neural Epitome Search For Architecture-agnostic Network Compression 6 6 3 2.00 Accept (Poster)
16 5.00 Efficient Riemannian Optimization On The Stiefel Manifold Via The Cayley Transform 6 3 6 2.00 Accept (Poster)
16 5.00 Federated Adversarial Domain Adaptation 6 3 6 2.00 Accept (Poster)
16 5.00 How To 0wn The Nas In Your Spare Time 6 3 6 2.00 Accept (Poster)
16 5.00 Deep 3d Pan Via Local Adaptive “t-shaped” Convolutions With Global And Local Adaptive Dilations 3 6 6 2.00 Accept (Poster)
16 5.00 Efficient And Information-preserving Future Frame Prediction And Beyond 3 6 6 2.00 Accept (Poster)
16 5.00 Episodic Reinforcement Learning With Associative Memory 6 3 6 2.00 Accept (Poster)
16 5.00 Higher-order Function Networks For Learning Composable 3d Object Representations 6 3 6 2.00 Accept (Poster)
16 5.00 Atomnas: Fine-grained End-to-end Neural Architecture Search 3 6 6 2.00 Accept (Poster)
16 5.00 Learning Space Partitions For Nearest Neighbor Search 6 6 3 2.00 Accept (Poster)
16 5.00 Few-shot Learning On Graphs Via Super-classes Based On Graph Spectral Measures 6 3 6 2.00 Accept (Poster)
16 5.00 Nonlinearities In Activations Substantially Shape The Loss Surfaces Of Neural Networks 3 6 6 2.00 Accept (Poster)
16 5.00 Global Relational Models Of Source Code 6 3 6 2.00 Accept (Poster)
16 5.00 Improving Neural Language Generation With Spectrum Control 6 3 6 2.00 Accept (Poster)
16 5.00 Batchensemble: An Alternative Approach To Efficient Ensemble And Lifelong Learning 6 6 3 2.00 Accept (Poster)
16 5.00 Differentiable Programming For Physical Simulation 6 3 6 2.00 Accept (Poster)
16 5.00 Duration-of-stay Storage Assignment Under Uncertainty 6 3 6 2.00 Accept (Spotlight)
16 5.00 Locally Constant Networks 3 6 6 2.00 Accept (Poster)
16 5.00 Blockswap: Fisher-guided Block Substitution For Network Compression On A Budget 6 3 6 2.00 Accept (Poster)
16 5.00 Vl-bert: Pre-training Of Generic Visual-linguistic Representations 6 6 3 2.00 Accept (Poster)
16 5.00 Deep Symbolic Superoptimization Without Human Knowledge 6 3 6 2.00 Accept (Poster)
16 5.00 Automatically Discovering And Learning New Visual Categories With Ranking Statistics 6 6 3 2.00 Accept (Poster)
16 5.00 Semantically-guided Representation Learning For Self-supervised Monocular Depth 3 6 6 2.00 Accept (Poster)
17 4.67 Pure And Spurious Critical Points: A Geometric Study Of Linear Networks 3 3 8 5.56 Accept (Poster)
17 4.67 Ae-ot: A New Generative Model Based On Extended Semi-discrete Optimal Transport 3 8 3 5.56 Accept (Poster)
17 4.67 I Am Going Mad: Maximum Discrepancy Competition For Comparing Classifiers Adaptively 3 3 8 5.56 Accept (Poster)
17 4.67 Continual Learning With Adaptive Weights (claw) 3 8 3 5.56 Accept (Poster)
17 4.67 Logic And The 2-simplicial Transformer 8 3 3 5.56 Accept (Poster)
18 4.50 Sign-opt: A Query-efficient Hard-label Adversarial Attack 3 6 2.25 Accept (Poster)
18 4.50 Short And Sparse Deconvolution — A Geometric Approach 3 6 2.25 Accept (Poster)
19 4.33 Learning To Represent Programs With Property Signatures 1 6 6 5.56 Accept (Poster)
19 4.33 Disentangling Factors Of Variations Using Few Labels 6 6 1 5.56 Accept (Poster)
19 4.33 Empir: Ensembles Of Mixed Precision Deep Networks For Increased Robustness Against Adversarial Attacks 1 6 6 5.56 Accept (Poster)
19 4.33 Non-autoregressive Dialog State Tracking 6 1 6 5.56 Accept (Poster)
19 4.33 Going Beyond Token-level Pre-training For Embedding-based Large-scale Retrieval 1 6 6 5.56 Accept (Poster)
19 4.33 A Critical Analysis Of Self-supervision, Or What We Can Learn From A Single Image 6 1 6 5.56 Accept (Poster)
19 4.33 Overlearning Reveals Sensitive Attributes 6 1 6 5.56 Accept (Poster)
20 4.00 Exploratory Not Explanatory: Counterfactual Analysis Of Saliency Maps For Deep Rl 1 3 8 8.67 Accept (Poster)
20 4.00 Gap-aware Mitigation Of Gradient Staleness 6 3 3 2.00 Accept (Poster)
20 4.00 Input Complexity And Out-of-distribution Detection With Likelihood-based Generative Models 6 3 3 2.00 Accept (Poster)
20 4.00 Size-free Generalization Bounds For Convolutional Neural Networks 6 3 3 2.00 Accept (Poster)
20 4.00 Fair Resource Allocation In Federated Learning 3 3 6 2.00 Accept (Poster)
20 4.00 Dropedge: Towards Deep Graph Convolutional Networks On Node Classification 6 3 3 2.00 Accept (Poster)
20 4.00 Provable Filter Pruning For Efficient Neural Networks 3 6 3 2.00 Accept (Poster)
20 4.00 Playing The Lottery With Rewards And Multiple Languages: Lottery Tickets In Rl And Nlp 3 3 6 2.00 Accept (Poster)
21 3.33 Few-shot Text Classification With Distributional Signatures 6 1 3 4.22 Accept (Poster)
22 2.33 Efficient Probabilistic Logic Reasoning With Graph Neural Networks 1 3 3 0.89 Accept (Poster)