NeurIPS 2022

2,834 papers

Contact-aware Human Motion Forecasting

Wei Mao, miaomiao Liu, Richard I Hartley, Mathieu Salzmann

Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning

Yejia Liu, Wang Zhu, Shaolei Ren

Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms

Surbhi Goel, Sham Kakade, Adam Kalai, Cyril Zhang

Outlier-Robust Sparse Estimation via Non-Convex Optimization

Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane

Fast Distance Oracles for Any Symmetric Norm

Yichuan Deng, Zhao Song, OMRI WEINSTEIN, Ruizhe Zhang

Fine-Grained Semantically Aligned Vision-Language Pre-Training

Juncheng Li, XIN HE, Longhui Wei, Long Qian, Linchao Zhu

A Kernelised Stein Statistic for Assessing Implicit Generative Models

Wenkai Xu, Gesine D Reinert

Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited

Mingguo He, Zhewei Wei, Ji-Rong Wen

Hamiltonian Latent Operators for content and motion disentanglement in image sequences

Asif Khan, Amos J. Storkey

TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction

Wei Lu, Qifeng Wu, Jixian Zhang, Jiahua Rao, Chengtao Li

Learning Interface Conditions in Domain Decomposition Solvers

Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott MacLachlan, Luke Olson

Physics-Informed Implicit Representations of Equilibrium Network Flows

Kevin D. Smith, Francesco Seccamonte, Ananthram Swami, Francesco Bullo

M2N: Mesh Movement Networks for PDE Solvers

Wenbin Song, Mingrui Zhang, Joseph G Wallwork, Junpeng Gao, Zheng Tian

Assaying Out-Of-Distribution Generalization in Transfer Learning

Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn

Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions

Kuan-Lin Chen, Harinath Garudadri, Bhaskar D Rao

ALMA: Hierarchical Learning for Composite Multi-Agent Tasks

Shariq Iqbal, Robby Costales, Fei Sha

SAGDA: Achieving O(ε^-2) Communication Complexity in Federated Min-Max Learning

Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu

On the convergence of policy gradient methods to Nash equilibria in general stochastic games

Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil-Vasileios Vlatakis-Gkaragkounis

GULP: a prediction-based metric between representations

Enric Boix-Adsera, Hannah Lawrence, George Stepaniants, Philippe Rigollet

Mixture-of-Experts with Expert Choice Routing

Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang

Multi-layer State Evolution Under Random Convolutional Design

Mara Daniels, Cedric Gerbelot, Florent Krzakala, Lenka Zdeborová

Minimax Optimal Online Imitation Learning via Replay Estimation

Gokul Swamy, Nived Rajaraman, Matt Peng, Sanjiban Choudhury, J. A. Bagnell

Single Loop Gaussian Homotopy Method for Non-convex Optimization

Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda

SNAKE: Shape-aware Neural 3D Keypoint Field

Chengliang Zhong, Peixing You, Xiaoxue Chen, Hao Zhao, Fuchun Sun

When Does Group Invariant Learning Survive Spurious Correlations?

Yimeng Chen, Ruibin Xiong, Zhi-ming Ma, Yanyan Lan

Weighted Distillation with Unlabeled Examples

Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh

InsNet: An Efficient, Flexible, and Performant Insertion-based Text Generation Model

Sidi Lu, Tao Meng, Nanyun Peng

Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport

Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha

One-Inlier is First: Towards Efficient Position Encoding for Point Cloud Registration

Fan Yang, Lin Guo, Zhi Chen, Wenbing Tao

Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification

Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

FR: Folded Rationalization with a Unified Encoder

Wei Liu, Haozhao Wang, Jun Wang, Ruixuan Li, Chao Yue

Convexity Certificates from Hessians

Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty

Luning Sun, Daniel Huang, Hao Sun, Jian-Xun Wang

M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus

Lichao Zhang, Ruiqi Li, Shoutong Wang, Liqun Deng, Jinglin Liu

Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics

Lukas Prantl, Benjamin Ummenhofer, Vladlen Koltun, Nils Thuerey

Positively Weighted Kernel Quadrature via Subsampling

Satoshi Hayakawa, Harald Oberhauser, Terry Lyons

Formalizing Consistency and Coherence of Representation Learning

Harald Strömfelt, Luke Dickens, Artur Garcez, Alessandra Russo

Supervised Training of Conditional Monge Maps

Charlotte Bunne, Andreas Krause, Marco Cuturi

Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel

Changyong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling

Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation

Kristian Georgiev, Samuel Hopkins

Embodied Scene-aware Human Pose Estimation

Zhengyi Luo, Shun Iwase, Ye Yuan, Kris Kitani

Low-rank Optimal Transport: Approximation, Statistics and Debiasing

meyer scetbon, Marco Cuturi

Non-deep Networks

Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun

Set-based Meta-Interpolation for Few-Task Meta-Learning

Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang

Feature Learning in L_2-regularized DNNs: Attraction/Repulsion and Sparsity

Arthur Jacot, Eugene Golikov, Clement Hongler, Franck Gabriel

Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization

Aniket Das, Bernhard Schölkopf, Michael Muehlebach

Spatial Pruned Sparse Convolution for Efficient 3D Object Detection

Jianhui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan

When does dough become a bagel? Analyzing the remaining mistakes on ImageNet

Vijay Vasudevan, Benjamin Caine, Raphael Gontijo Lopes, Sara Fridovich-Keil, Rebecca Roelofs

CyCLIP: Cyclic Contrastive Language-Image Pretraining

Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan Rossi, Vishwa Vinay

A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions

Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye

Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons

Paul Bertens, Seong-Whan Lee

Leveraging Inter-Layer Dependency for Post -Training Quantization

changbao wang, DanDan Zheng, Yuanliu Liu, Liang Li

Online Neural Sequence Detection with Hierarchical Dirichlet Point Process

Weihan Li, Yu Qi, Gang Pan

A consistently adaptive trust-region method

Fadi Hamad, Oliver Hinder

AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness

Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang

Exact learning dynamics of deep linear networks with prior knowledge

Lukas Braun, Clémentine Dominé, James Fitzgerald, Andrew Saxe

Revisiting Active Sets for Gaussian Process Decoders

Pablo Moreno-Muñoz, Cilie Feldager, Søren Hauberg

Conformal Frequency Estimation with Sketched Data

Matteo Sesia, Stefano Favaro

Feature-Proxy Transformer for Few-Shot Segmentation

Jian-Wei Zhang, Yifan Sun, Yi Yang, Wei Chen

First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces

Michael I. Jordan, Tianyi Lin, Emmanouil-Vasileios Vlatakis-Gkaragkounis

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos

Motion Transformer with Global Intention Localization and Local Movement Refinement

Shaoshuai Shi, Li Jiang, Dengxin Dai, Bernt Schiele

Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture

Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du

Adversarial Robustness is at Odds with Lazy Training

Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora

Paraphrasing Is All You Need for Novel Object Captioning

Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency

On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood

Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford

RényiCL: Contrastive Representation Learning with Skew Rényi Divergence

Kyungmin Lee, Jinwoo Shin

Procedural Image Programs for Representation Learning

Manel Baradad, Richard Chen, Jonas Wulff, Tongzhou Wang, Rogerio Feris

Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability

Whiyoung Jung, Myungsik Cho, Jongeui Park, Youngchul Sung

Randomized Sketches for Clustering: Fast and Optimal Kernel k-Means

Rong Yin, Yong Liu, Weiping Wang, Dan Meng

Equivariant Networks for Zero-Shot Coordination

Darius Muglich, Christian Schroeder de Witt, Elise van der Pol, Shimon Whiteson, Jakob Foerster

Few-shot Relational Reasoning via Connection Subgraph Pretraining

Qian Huang, Hongyu Ren, Jure Leskovec

On the Robustness of Graph Neural Diffusion to Topology Perturbations

Yang Song, Qiyu Kang, Sijie Wang, KAI ZHAO, Wee Peng Tay

Defending Against Adversarial Attacks via Neural Dynamic System

Xiyuan Li, Zou Xin, Weiwei Liu

Near-Optimal Randomized Exploration for Tabular Markov Decision Processes

Zhihan Xiong, Ruoqi Shen, Qiwen Cui, Maryam Fazel, Simon S Du

Learning Contrastive Embedding in Low-Dimensional Space

Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu

Online Allocation and Learning in the Presence of Strategic Agents

Steven Yin, Shipra Agrawal, Assaf J. Zeevi

Meta-Learning with Self-Improving Momentum Target

Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin

Disentangling Transfer in Continual Reinforcement Learning

Maciej Wolczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś

Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions

Audrey Huang, Nan Jiang

Self-supervised Amodal Video Object Segmentation

Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He

A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data

Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song

Semantic uncertainty intervals for disentangled latent spaces

Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola

AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments

Sudipta Paul, Amit Roy-Chowdhury, Anoop Cherian

SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG

Reinmar Kobler, Jun-ichiro Hirayama, Qibin Zhao, Motoaki Kawanabe

Test Time Adaptation via Conjugate Pseudo-labels

Sachin Goyal, Mingjie Sun, Aditi Raghunathan, J. Zico Kolter

Geodesic Self-Attention for 3D Point Clouds

Zhengyu Li, XUAN TANG, Zihao Xu, Xihao Wang, Hui Yu

Surprise Minimizing Multi-Agent Learning with Energy-based Models

Karush Suri, Xiao Qi Shi, Konstantinos N Plataniotis, Yuri Lawryshyn

Falsification before Extrapolation in Causal Effect Estimation

Zeshan M Hussain, Michael Oberst, Ming-Chieh Shih, David Sontag

Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity

Bingqing Song, Ioannis Tsaknakis, Chung-Yiu Yau, Hoi-To Wai, Mingyi Hong

360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning

Bolivar Solarte, Chin-Hsuan Wu, Yueh-Cheng Liu, Yi-Hsuan Tsai, Min Sun

Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline

Penghao Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li

GraphQNTK: Quantum Neural Tangent Kernel for Graph Data

Yehui Tang, Junchi Yan

Biologically Inspired Dynamic Thresholds for Spiking Neural Networks

Jianchuan Ding, Bo Dong, Felix Heide, Yufei Ding, Yunduo Zhou

Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift

Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin

A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning

Zhenyu Sun, Ermin Wei

Imitating Past Successes can be Very Suboptimal

Benjamin Eysenbach, Soumith Udatha, Ruslan Salakhutdinov, Sergey Levine

Natural image synthesis for the retina with variational information bottleneck representation

Babak Rahmani, Demetri Psaltis, Christophe Moser

High-Order Pooling for Graph Neural Networks with Tensor Decomposition

Chenqing Hua, Guillaume Rabusseau, Jian Tang

OpenFWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion

Chengyuan Deng, Shihang Feng, Hanchen Wang, Xitong Zhang, Peng Jin