NeurIPS 2021

2,334 papers

Property-Aware Relation Networks for Few-Shot Molecular Property Prediction

Yaqing Wang, Abulikemu Abuduweili, Quanming Yao, Dejing Dou

PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning

Yining Hong, Li Yi, Josh Tenenbaum, Antonio Torralba, Chuang Gan

Scatterbrain: Unifying Sparse and Low-rank Attention

Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra

Dense Keypoints via Multiview Supervision

Zhixuan Yu, Haozheng Yu, Long Sha, Sujoy Ganguly, Hyun Soo Park

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Bowen Zhang, Yifan liu, Zhi Tian, Chunhua Shen

Boosting with Multiple Sources

Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh

Coresets for Clustering with Missing Values

Vladimir braverman, Shaofeng Jiang, Robert Krauthgamer, Xuan Wu

Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning

Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm

Privately Publishable Per-instance Privacy

Rachel Redberg, Yu-Xiang Wang

Evaluating model performance under worst-case subpopulations

Mike Li, Hongseok Namkoong, Shangzhou Xia

Causal Inference for Event Pairs in Multivariate Point Processes

Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei

Risk-Aware Transfer in Reinforcement Learning using Successor Features

Michael Gimelfarb, Andre Barreto, Scott Sanner, Chi-Guhn Lee

Formalizing the Generalization-Forgetting Trade-off in Continual Learning

Krishnan Raghavan, Prasanna Balaprakash

Provably Strict Generalisation Benefit for Invariance in Kernel Methods

Bryn Elesedy

Topological Detection of Trojaned Neural Networks

Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen

Invertible DenseNets with Concatenated LipSwish

Yura Perugachi-Diaz, Jakub Tomczak, Sandjai Bhulai

Risk-averse Heteroscedastic Bayesian Optimization

Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause

Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation

Ying Sun, Hengshu Zhu, Chuan Qin, Fuzhen Zhuang, Qing He

Mining the Benefits of Two-stage and One-stage HOI Detection

Aixi Zhang, Yue Liao, Si Liu, Miao Lu, Yongliang Wang

A Prototype-Oriented Framework for Unsupervised Domain Adaptation

Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang

Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs

Tao Liu, Ruida Zhou, Dileep Kalathil, Panganamala Kumar, Chao Tian

On the Representation Power of Set Pooling Networks

Christian Bueno, Alan Hylton

Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels

Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee W. Teh

Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck

Junho Kim, Byung-Kwan Lee, Yong Man Ro

Good Classification Measures and How to Find Them

Martijn Gösgens, Anton Zhiyanov, Aleksey Tikhonov, Liudmila Prokhorenkova

Differentiable Simulation of Soft Multi-body Systems

Junbang Liang, Vladlen Koltun, Ming Lin, Yi-Ling Qiao, Yiling Qiao

Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning

Christopher Rytting, David Wingate

Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency

Anish Chakrabarty, Swagatam Das

Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Ge Yang, Edward Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu

Relaxing Local Robustness

Klas Leino, Matt Fredrikson

NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform

Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines

Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck

Nicolas Skatchkovsky, Osvaldo Simeone, Hyeryung Jang

An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning

Tianpei Yang, Weixun Wang, Hongyao Tang, Jianye Hao, Zhaopeng Meng

ProTo: Program-Guided Transformer for Program-Guided Tasks

Zelin Zhao, Karan Samel, Binghong Chen, lee song

Dynamic Bottleneck for Robust Self-Supervised Exploration

Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao

Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence

Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection

HanQin Cai, Jialin Liu, Wotao Yin

Adversarial Regression with Doubly Non-negative Weighting Matrices

Tam Le, Truyen Nguyen, Makoto Yamada, Jose Blanchet, Viet Anh Nguyen

Scalable Online Planning via Reinforcement Learning Fine-Tuning

Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart J. Russell, Noam Brown

Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation

Yufei Wang, Can Xu, Huang Hu, Chongyang Tao, Stephen Wan

Towards Robust and Reliable Algorithmic Recourse

Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju

Adversarial Neuron Pruning Purifies Backdoored Deep Models

Dongxian Wu, Yisen Wang

Dynamic population-based meta-learning for multi-agent communication with natural language

Abhinav Gupta, Marc Lanctot, Angeliki Lazaridou

A Faster Maximum Cardinality Matching Algorithm with Applications in Machine Learning

Nathaniel Lahn, Sharath Raghvendra, Jiacheng Ye

Designing Counterfactual Generators using Deep Model Inversion

Jayaraman Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jia Liang, Akshay Chaudhari

Graph Differentiable Architecture Search with Structure Learning

Yijian Qin, Xin Wang, Zeyang Zhang, Wenwu Zhu

Recovering Latent Causal Factor for Generalization to Distributional Shifts

Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen

A unified framework for bandit multiple testing

Ziyu Xu, Ruodu Wang, Aaditya Ramdas

Joint inference and input optimization in equilibrium networks

Swaminathan Gurumurthy, Shaojie Bai, Zachary Manchester, J. Zico Kolter

On Linear Stability of SGD and Input-Smoothness of Neural Networks

Chao Ma, Lexing Ying

Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks

Xingsi Dong, Tianhao Chu, Tiejun Huang, Zilong Ji, Si Wu

Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space

Jiehong Lin, Hongyang Li, Ke Chen, Jiangbo Lu, Kui Jia

Large-Scale Unsupervised Object Discovery

Van Huy Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, Jean Ponce

Linear Convergence of Gradient Methods for Estimating Structured Transition Matrices in High-dimensional Vector Autoregressive Models

Xiao Lv, Wei Cui, Yulong Liu

Information Directed Sampling for Sparse Linear Bandits

Botao Hao, Tor Lattimore, Wei Deng

Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent

Priyank Jaini, Lars Holdijk, Max Welling

Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds

Antonios Antoniadis, Christian Coester, Marek Elias, Adam Polak, Bertrand Simon

Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems

Jimmy Smith, Scott Linderman, David Sussillo

Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels

Jizong Peng, Ping Wang, Christian Desrosiers, Marco Pedersoli

Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting

Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei

Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems

Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

Low-Rank Subspaces in GANs

Jiapeng Zhu, Ruili Feng, Yujun Shen, Deli Zhao, Zheng-Jun Zha

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes

Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Horvath, Theodoros Damoulas

HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning

Shiming Chen, Guosen Xie, Yang Liu, Qinmu Peng, Baigui Sun

An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning

Cyrus Cousins

Neural Bootstrapper

Minsuk Shin, Hyungjoo Cho, Hyun-seok Min, Sungbin Lim

Neural Dubber: Dubbing for Videos According to Scripts

Chenxu Hu, Qiao Tian, Tingle Li, Wang Yuping, Yuxuan Wang

Few-Shot Object Detection via Association and DIscrimination

Yuhang Cao, Jiaqi Wang, Ying Jin, Tong Wu, Kai Chen

DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras

Zachary Teed, Jia Deng

Global-aware Beam Search for Neural Abstractive Summarization

Ye Ma, Zixun Lan, Lu Zong, Kaizhu Huang

Differentiable Multiple Shooting Layers

Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park

Learning with Algorithmic Supervision via Continuous Relaxations

Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

On Joint Learning for Solving Placement and Routing in Chip Design

Ruoyu Cheng, Junchi Yan

Multimodal Virtual Point 3D Detection

Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl

Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction

Konstantin Schürholt, Dimche Kostadinov, Damian Borth

Instance-Conditional Knowledge Distillation for Object Detection

Zijian Kang, Peizhen Zhang, Xiangyu Zhang, Jian Sun, Nanning Zheng

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style

Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf

Online Learning Of Neural Computations From Sparse Temporal Feedback

Lukas Braun, TIm Vogels

Capacity and Bias of Learned Geometric Embeddings for Directed Graphs

Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L Clarkson

GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training

Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang

Uncertainty-Driven Loss for Single Image Super-Resolution

Qian Ning, Weisheng Dong, Xin Li, Jinjian Wu, GUANGMING Shi

Noether Networks: meta-learning useful conserved quantities

Ferran Alet, Dylan Doblar, Allan Zhou, Josh Tenenbaum, Kenji Kawaguchi

Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection

Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric

Neural optimal feedback control with local learning rules

Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan Sengupta

Deep Molecular Representation Learning via Fusing Physical and Chemical Information

Shuwen Yang, Ziyao Li, Guojie Song, Lingsheng Cai

EditGAN: High-Precision Semantic Image Editing

huan ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba

Adaptive Machine Unlearning

Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi

Rethinking the Pruning Criteria for Convolutional Neural Network

Zhongzhan Huang, Wenqi Shao, Xinjiang Wang, Liang Lin, Ping Luo

Introspective Distillation for Robust Question Answering

Yulei Niu, Hanwang Zhang

Diffusion Normalizing Flow

Qinsheng Zhang, Yongxin Chen

Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation

Fenglin Liu, Chenyu You, Xian Wu, Shen Ge, Sheng wang

Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations

Hyeong-Seok Choi, Juheon Lee, Wansoo Kim, Jie Lee, Hoon Heo

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations

Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Luc V Gool

Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD

Rémi Bardenet, Subhroshekhar Ghosh, Meixia LIN

Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training

Lue Tao, Lei Feng, Jinfeng Yi, Sheng-jun Huang, Songcan Chen

Counterfactual Invariance to Spurious Correlations in Text Classification

Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein

Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi

Ho Chit Siu, Jaime Peña, Edenna Chen, Yutai Zhou, Victor Lopez

Learning Diverse Policies in MOBA Games via Macro-Goals

Yiming Gao, Bei Shi, Xueying Du, Liang Wang, Guangwei Chen

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning

Colin Wei, Sang Michael Xie, Tengyu Ma

Deformable Butterfly: A Highly Structured and Sparse Linear Transform

Rui Lin, Jie Ran, King Hung Chiu, Graziano Chesi, Ngai Wong