NeurIPS 2022

2,834 papers

On the Strong Correlation Between Model Invariance and Generalization

Weijian Deng, Stephen Gould, Liang Zheng

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies

Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari

Segmenting Moving Objects via an Object-Centric Layered Representation

Junyu Xie, Weidi Xie, Andrew Zisserman

A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets

Miri Zilka, Bradley Butcher, Adrian Weller

Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers

Jian Wang, Miaomiao Zhang

ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery

Andaç Demir, Baris Coskunuzer, Yulia Gel, Ignacio Segovia-Dominguez, Yuzhou Chen

Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias

Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

Flexible Diffusion Modeling of Long Videos

William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood

Improving Transformer with an Admixture of Attention Heads

Tan Nguyen, Tam Nguyen, Hai Do, Khai Nguyen, Vishwanath Saragadam

Multi-Game Decision Transformers

Kuang-Huei Lee, Ofir Nachum, Mengjiao (Sherry) Yang, Lisa Lee, Daniel Freeman

Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights

Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth

A Reparametrization-Invariant Sharpness Measure Based on Information Geometry

Cheongjae Jang, Sungyoon Lee, Frank Park, Yung-kyun Noh

Receding Horizon Inverse Reinforcement Learning

Yiqing Xu, Wei Gao, David Hsu

MATE: Benchmarking Multi-Agent Reinforcement Learning in Distributed Target Coverage Control

Xuehai Pan, Mickel Liu, Fangwei Zhong, Yaodong Yang, Song-chun Zhu

Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders

Olivier Jeunen, Ciarán Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas

Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records

Hongda Sun, Shufang Xie, Shuqi Li, Yuhan Chen, Ji-Rong Wen

Hedging as Reward Augmentation in Probabilistic Graphical Models

Debarun Bhattacharjya, Radu Marinescu

Power and limitations of single-qubit native quantum neural networks

Zhan Yu, Hongshun Yao, Mujin Li, Xin Wang

Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning

Alex Chan, Mihaela van der Schaar

PlasticityNet: Learning to Simulate Metal, Sand, and Snow for Optimization Time Integration

Xuan Li, Yadi Cao, Minchen Li, Yin Yang, Craig Schroeder

Provably tuning the ElasticNet across instances

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

Non-rigid Point Cloud Registration with Neural Deformation Pyramid

Yang Li, Tatsuya Harada

Byzantine Spectral Ranking

Arnhav Datar, Arun Rajkumar, John Augustine

Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright

Unsupervised Adaptation from Repeated Traversals for Autonomous Driving

Yurong You, Cheng Perng Phoo, Katie Luo, Travis Zhang, Wei-Lun Chao

Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors

Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu

Fair Bayes-Optimal Classifiers Under Predictive Parity

Xianli Zeng, Edgar Dobriban, Guang Cheng

Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks

Frank Nussbaum, Jakob Gawlikowski, Julia Niebling

Explaining Preferences with Shapley Values

Robert Hu, Siu Lun Chau, Jaime Ferrando Huertas, Dino Sejdinovic

Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning

Joseph Early, Tom Bewley, Christine Evers, Sarvapali Ramchurn

Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees

Wenying Deng, Beau Coker, Rajarshi Mukherjee, Jeremiah Liu, Brent Coull

Parameter-free Dynamic Graph Embedding for Link Prediction

Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang

Safe Opponent-Exploitation Subgame Refinement

Mingyang Liu, Chengjie Wu, Qihan Liu, Yansen Jing, Jun Yang

QUARK: Controllable Text Generation with Reinforced Unlearning

Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, LIANHUI Qin

Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization

Yibo Zeng, Henry Lam

DOMINO: Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning

Yao Mu, Yuzheng Zhuang, Fei Ni, Bin Wang, Jianyu Chen

Local Identifiability of Deep ReLU Neural Networks: the Theory

Joachim Bona-Pellissier, François Malgouyres, Francois Bachoc

CUP: Critic-Guided Policy Reuse

Jin Zhang, Siyuan Li, Chongjie Zhang

Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models

Haoyue Dai, Peter Spirtes, Kun Zhang

Robust Calibration with Multi-domain Temperature Scaling

Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Jordan

Improved Algorithms for Neural Active Learning

Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He

Change Event Dataset for Discovery from Spatio-temporal Remote Sensing Imagery

Utkarsh Mall, Bharath Hariharan, Kavita Bala

Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset

Yang Fu, Xiaolong Wang

Grow and Merge: A Unified Framework for Continuous Categories Discovery

Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao

ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine

Ilker Demirel, Ahmet Alparslan Celik, Cem Tekin

Effectiveness of Vision Transformer for Fast and Accurate Single-Stage Pedestrian Detection

Jing Yuan, Panagiotis Barmpoutis, Tania Stathaki

mRI: Multi-modal 3D Human Pose Estimation Dataset using mmWave, RGB-D, and Inertial Sensors

Sizhe An, Yin Li, Umit Ogras

Is Integer Arithmetic Enough for Deep Learning Training?

Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian, Masoud Asgharian, Vahid Partovi Nia

NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification

Qitian Wu, Wentao Zhao, Zenan Li, Junchi Yan, David P. Wipf

Autoregressive Perturbations for Data Poisoning

Pedro Sandoval-Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein

Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network

SIQI LIANG, Yan Sun, Faming Liang

Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks

Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov

Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks

Anders Aamand, Justin Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld

Support Recovery in Sparse PCA with Incomplete Data

Hanbyul Lee, Qifan Song, Jean Honorio

Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking

Ruofan Wu, Junmin Zhong, Brent Wallace, Xiang Gao, He Huang

Forecasting Future World Events With Neural Networks

Andy Zou, Tristan Xiao, Ryan Jia, Joe Kwon, Mantas Mazeika

First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data

Mao Ye, Lemeng Wu, Qiang Liu

Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation

Yixiong Zou, Shanghang Zhang, Yuhua Li, Ruixuan Li

NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation

Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim, Jinwoo Shin

ProtoX: Explaining a Reinforcement Learning Agent via Prototyping

Ronilo Ragodos, Tong Wang, Qihang Lin, Xun Zhou

Imbalance Trouble: Revisiting Neural-Collapse Geometry

CHRISTOS THRAMPOULIDIS, Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia

Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors

Eric Wu, Nora Brackbill, Alexander Sher, Alan Litke, Eero P. Simoncelli

Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse

Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh

Simplified Graph Convolution with Heterophily

Sudhanshu Chanpuriya, Cameron Musco

ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers

Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks

Arian Jamasb, Ramon Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris

Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors

Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang

How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders

Qi Zhang, Yifei Wang, Yisen Wang

CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition

Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo

Self-Supervised Fair Representation Learning without Demographics

Junyi Chai, Xiaoqian Wang

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap

Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová

Exploring Example Influence in Continual Learning

Qing Sun, Fan Lyu, Fanhua Shang, Wei Feng, Liang Wan

Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training

Renrui Zhang, Ziyu Guo, peng gao, Rongyao Fang, Bin Zhao

Associating Objects and Their Effects in Video through Coordination Games

Erika Lu, Forrester Cole, Weidi Xie, Tali Dekel, Bill Freeman

Movement Penalized Bayesian Optimization with Application to Wind Energy Systems

Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs

Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu

Tensor Wheel Decomposition and Its Tensor Completion Application

Zhong-Cheng Wu, Ting-Zhu Huang, Liang-Jian Deng, Hong-Xia Dou, Deyu Meng

Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics

Harsh Rangwani, shrinivas ramasubramanian, Sho Takemori, Kato Takashi, Yuhei Umeda

Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study

Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

Faster and Scalable Algorithms for Densest Subgraph and Decomposition

Elfarouk Harb, Kent Quanrud, Chandra Chekuri

MORA: Improving Ensemble Robustness Evaluation with Model Reweighing Attack

yunrui yu, Xitong Gao, Cheng-Zhong Xu

Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution

Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou

Learning from Label Proportions by Learning with Label Noise

Jianxin Zhang, Yutong Wang, Clay Scott

What are the best Systems? New Perspectives on NLP Benchmarking

Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon

Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm

Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski

Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations

Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma

PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation

Maxwell Xu, Alexander Moreno, Supriya Nagesh, Varol Aydemir, David Wetter

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design

Jörg Franke, Frederic Runge, Frank Hutter

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens

Elad Ben Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach

Learning General World Models in a Handful of Reward-Free Deployments

Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip Ball, Oleh Rybkin

Relation-Constrained Decoding for Text Generation

Xiang Chen, Zhixian Yang, Xiaojun Wan

Top Two Algorithms Revisited

Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann

Generalization Gap in Amortized Inference

Mingtian Zhang, Peter Hayes, David Barber

Does Momentum Change the Implicit Regularization on Separable Data?

Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen

Trading off Image Quality for Robustness is not Necessary with Regularized Deterministic Autoencoders

Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper

The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models

Conglong Li, Minjia Zhang, Yuxiong He

Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems

Jan Harold Alcantara, Ching-pei Lee

Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution

Leon Hetzel, Simon Boehm, Niki Kilbertus, Stephan Günnemann, mohammad lotfollahi

A framework for bilevel optimization that enables stochastic and global variance reduction algorithms

Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau

Subgame Solving in Adversarial Team Games

Brian Zhang, Luca Carminati, Federico Cacciamani, Gabriele Farina, Pierriccardo Olivieri