NeurIPS 2021

2,334 papers

DualNet: Continual Learning, Fast and Slow

Quang Pham, Chenghao Liu, Steven C. Hoi

Generalizable Imitation Learning from Observation via Inferring Goal Proximity

Youngwoon Lee, Andrew Szot, Shao-Hua Sun, Joseph J. Lim

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning

Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo

Multi-armed Bandit Requiring Monotone Arm Sequences

Ningyuan Chen

CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings

Tatiana Likhomanenko, Qiantong Xu, Gabriel Synnaeve, Ronan Collobert, Alex Rogozhnikov

Active 3D Shape Reconstruction from Vision and Touch

Edward Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik

Class-Disentanglement and Applications in Adversarial Detection and Defense

Kaiwen Yang, Tianyi Zhou, Yonggang Zhang, Xinmei Tian, Dacheng Tao

Safe Pontryagin Differentiable Programming

Wanxin Jin, Shaoshuai Mou, George J. Pappas

Adversarial Attack Generation Empowered by Min-Max Optimization

Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu

Assessing Fairness in the Presence of Missing Data

Yiliang Zhang, Qi Long

Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic

Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang

Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification

Walter Gerych, Tom Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner

Probabilistic Tensor Decomposition of Neural Population Spiking Activity

Hugo Soulat, Sepiedeh Keshavarzi, Troy Margrie, Maneesh Sahani

Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework

Tengteng Huang, Yifan Sun, Xun Wang, Haotian Yao, Chi Zhang

Contrastive Reinforcement Learning of Symbolic Reasoning Domains

Gabriel Poesia, WenXin Dong, Noah Goodman

Online Control of Unknown Time-Varying Dynamical Systems

Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan

Adversarial Graph Augmentation to Improve Graph Contrastive Learning

Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville

Transformer in Transformer

Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing XU

DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples

Yi Xu, Jiandong Ding, Lu Zhang, Shuigeng Zhou

On Inductive Biases for Heterogeneous Treatment Effect Estimation

Alicia Curth, Mihaela van der Schaar

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction

ZAIXI ZHANG, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee

Rethinking Neural Operations for Diverse Tasks

Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Re

A Computationally Efficient Method for Learning Exponential Family Distributions

Abhin Shah, Devavrat Shah, Gregory Wornell

Doubly Robust Thompson Sampling with Linear Payoffs

Wonyoung Kim, Gi-Soo Kim, Myunghee Cho Paik

Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding

Yang Li, Si Si, Gang Li, Cho-jui Hsieh, Samy Bengio

A flow-based latent state generative model of neural population responses to natural images

Mohammad Bashiri, Edgar Walker, Konstantin-Klemens Lurz, Akshay Jagadish, Taliah Muhammad

FLEX: Unifying Evaluation for Few-Shot NLP

Jonathan Bragg, Arman Cohan, Kyle Lo, Iz Beltagy

On Blame Attribution for Accountable Multi-Agent Sequential Decision Making

Stelios Triantafyllou, Adish Singla, Goran Radanovic

Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables

Jakob Runge

Multimodal and Multilingual Embeddings for Large-Scale Speech Mining

Paul-Ambroise Duquenne, Hongyu Gong, Holger Schwenk

Nested Graph Neural Networks

Muhan Zhang, Pan Li

A nonparametric method for gradual change problems with statistical guarantees

Lizhen Nie, Dan Nicolae

Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs

Han Zhong, Jiayi Huang, Lin Yang, Liwei Wang

The decomposition of the higher-order homology embedding constructed from the k-Laplacian

Yu-Chia Chen, Marina Meila

Revisiting the Calibration of Modern Neural Networks

Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai

Iterative Amortized Policy Optimization

Joseph Marino, Alexandre Piche, Alessandro Davide Ialongo, Yisong Yue

Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision Processes

HyunJi Alex Nam, Scott Fleming, Emma Brunskill

Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach

Ahmed Abbas, Paul Swoboda

Nearly Horizon-Free Offline Reinforcement Learning

Tongzheng Ren, Jialian Li, Bo Dai, Simon S Du, Sujay Sanghavi

Unsupervised Learning of Compositional Energy Concepts

Yilun Du, Shuang Li, Yash Sharma, Josh Tenenbaum, Igor Mordatch

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception

Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David Cox

Dimensionality Reduction for Wasserstein Barycenter

Zachary Izzo, Sandeep Silwal, Samson Zhou

Representing Hyperbolic Space Accurately using Multi-Component Floats

Tao Yu, Christopher M De Sa

CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age

Dani Kiyasseh, Tingting Zhu, David Clifton

Self-Supervised Learning with Kernel Dependence Maximization

Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton

Neural Algorithmic Reasoners are Implicit Planners

Andreea-Ioana Deac, Petar Veličković, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang

Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL

Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts, Stephen J Roberts

Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions

Jiachen Sun, Yulong Cao, Christopher B Choy, Zhiding Yu, Anima Anandkumar

Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams

Chawin Sitawarin, Evgenios Kornaropoulos, Dawn Song, David Wagner

ResT: An Efficient Transformer for Visual Recognition

Qinglong Zhang, Yu-Bin Yang

Regularization in ResNet with Stochastic Depth

Soufiane Hayou, Fadhel Ayed

Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction

Jing Zhang, Jianwen Xie, Nick Barnes, Ping Li

Federated Multi-Task Learning under a Mixture of Distributions

Othmane MARFOQ, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal

Directional Message Passing on Molecular Graphs via Synthetic Coordinates

Johannes Gasteiger, Chandan Yeshwanth, Stephan Günnemann

Neural Circuit Synthesis from Specification Patterns

Frederik Schmitt, Christopher Hahn, Markus N Rabe, Bernd Finkbeiner

Overinterpretation reveals image classification model pathologies

Brandon Carter, Siddhartha Jain, Jonas W Mueller, David Gifford

A Theoretical Analysis of Fine-tuning with Linear Teachers

Gal Shachaf, Alon Brutzkus, Amir Globerson

Leveraging SE(3) Equivariance for Self-supervised Category-Level Object Pose Estimation from Point Clouds

Xiaolong Li, Yijia Weng, Li Yi, Leonidas Guibas, A. Abbott

Label Disentanglement in Partition-based Extreme Multilabel Classification

Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-jui Hsieh, Inderjit S Dhillon

Identifying and Benchmarking Natural Out-of-Context Prediction Problems

David Madras, Richard S. Zemel

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance

Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leora Horwitz

Augmented Shortcuts for Vision Transformers

Yehui Tang, Kai Han, Chang Xu, An Xiao, Yiping Deng

Attention Approximates Sparse Distributed Memory

Trenton Bricken, Cengiz Pehlevan

Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings

Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu

Unadversarial Examples: Designing Objects for Robust Vision

Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry

Who Leads and Who Follows in Strategic Classification?

Tijana Zrnic, Eric Mazumdar, Shankar Sastry, Michael I. Jordan

Large-Scale Wasserstein Gradient Flows

Petr Mokrov, Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M Solomon

Learning to Ground Multi-Agent Communication with Autoencoders

Toru Lin, Jacob Huh, Christopher Stauffer, Ser Nam Lim, Phillip Isola

Efficient Neural Network Training via Forward and Backward Propagation Sparsification

Xiao Zhou, Weizhong Zhang, Zonghao Chen, SHIZHE DIAO, Tong Zhang

Neural Relightable Participating Media Rendering

Quan Zheng, Gurprit Singh, Hans-peter Seidel

Structured Dropout Variational Inference for Bayesian Neural Networks

Son Nguyen, Duong Nguyen, Khai Nguyen, Khoat Than, Hung Bui

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks

Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai

Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II

Yossi Arjevani, Michael Field

PettingZoo: Gym for Multi-Agent Reinforcement Learning

J KTerry, Benjamin Black, Nathaniel Grammel, Mario Jayakumar, Ananth Hari

Random Shuffling Beats SGD Only After Many Epochs on Ill-Conditioned Problems

Itay Safran, Ohad Shamir

Automorphic Equivalence-aware Graph Neural Network

Fengli Xu, Quanming Yao, Pan Hui, Yong Li

TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework

Shun Lu, Jixiang Li, Jianchao Tan, Sen Yang, Ji Liu

Deep Extended Hazard Models for Survival Analysis

Qixian Zhong, Jonas W Mueller, Jane-Ling Wang

Probability Paths and the Structure of Predictions over Time

Zhiyuan Jerry Lin, Hao Sheng, Sharad Goel

Decision Transformer: Reinforcement Learning via Sequence Modeling

Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover

Uncertain Decisions Facilitate Better Preference Learning

Cassidy Laidlaw, Stuart J. Russell

Learning-to-learn non-convex piecewise-Lipschitz functions

Maria-Florina F Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar

Parametric Complexity Bounds for Approximating PDEs with Neural Networks

Tanya Marwah, Zachary Lipton, Andrej Risteski

Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models

Matej Zečević, Devendra Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting

Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable

Tian-Zuo Wang, Zhi-Hua Zhou

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions

Huangjie Zheng, Mingyuan Zhou

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles

Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang

DOBF: A Deobfuscation Pre-Training Objective for Programming Languages

Marie-Anne Lachaux, Baptiste Roziere, Marc Szafraniec, Guillaume Lample

H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion

Hongyi Xu, Thiemo Alldieck, Cristian Sminchisescu

Robust Compressed Sensing MRI with Deep Generative Priors

Ajil Jalal, Marius Arvinte, Giannis Daras, ecprice, Alexandros G Dimakis

Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks

Qiyu Kang, Yang Song, Qinxu Ding, Wee Peng Tay

Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models

Keunseo Kim, JunCheol Shin, Heeyoung Kim

Anti-Backdoor Learning: Training Clean Models on Poisoned Data

Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li

Graph Adversarial Self-Supervised Learning

Longqi Yang, Liangliang Zhang, Wenjing Yang

M-FAC: Efficient Matrix-Free Approximations of Second-Order Information

Elias Frantar, Eldar Kurtic, Dan Alistarh

Adversarial Reweighting for Partial Domain Adaptation

Xiang Gu, Xi Yu, yan yang, Jian Sun, Zongben Xu

Embedding Principle of Loss Landscape of Deep Neural Networks

Yaoyu Zhang, Zhongwang Zhang, Tao Luo, Zhiqin J Xu

Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples

Kanghyun Choi, Deokki Hong, Noseong Park, Youngsok Kim, Jinho Lee

Characterizing the risk of fairwashing

Ulrich Aïvodji, Hiromi Arai, Sébastien Gambs, Satoshi Hara

Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling

Naoya Takeishi, Alexandros Kalousis