ICLR 2023

1,573 papers

Learning Probabilistic Topological Representations Using Discrete Morse Theory

Xiaoling Hu, Dimitris Samaras, Chao Chen

Localized Randomized Smoothing for Collective Robustness Certification

Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, Stephan Günnemann

ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion

Aleksandar Pavlović, Emanuel Sallinger

UNICORN: A Unified Backdoor Trigger Inversion Framework

Zhenting Wang, Kai Mei, Juan Zhai, Shiqing Ma

Revisiting adapters with adversarial training

Sylvestre-Alvise Rebuffi, Francesco Croce, Sven Gowal

A Higher Precision Algorithm for Computing the $1$-Wasserstein Distance

Pankaj K Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Rachita Sowle

Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation

Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar

Neuromechanical Autoencoders: Learning to Couple Elastic and Neural Network Nonlinearity

Deniz Oktay, Mehran Mirramezani, Eder Medina, Ryan P Adams

Self-supervised learning with rotation-invariant kernels

Léon Zheng, Gilles Puy, Elisa Riccietti, Patrick Pérez, Remi Gribonval

VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation

Thanh Nguyen-Tang, Raman Arora

Spectral Augmentation for Self-Supervised Learning on Graphs

Lu Lin, Jinghui Chen, Hongning Wang

Emergence of Maps in the Memories of Blind Navigation Agents

Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos

Learning Fair Graph Representations via Automated Data Augmentations

Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou

Learning About Progress From Experts

Jake Bruce, Ankit Anand, Bogdan Mazoure, Rob Fergus

Choreographer: Learning and Adapting Skills in Imagination

Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar

Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries

Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas

Proposal-Contrastive Pretraining for Object Detection from Fewer Data

Quentin Bouniot, Romaric Audigier, Angélique Loesch, Amaury Habrard

Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics

Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker

A probabilistic framework for task-aligned intra- and inter-area neural manifold estimation

Edoardo Balzani, Jean-Paul G Noel, Pedro Herrero-Vidal, Dora E Angelaki, Cristina Savin

Hebbian Deep Learning Without Feedback

Adrien Journé, Hector Garcia Rodriguez, Qinghai Guo, Timoleon Moraitis

Can We Find Nash Equilibria at a Linear Rate in Markov Games?

Zhuoqing Song, Jason D. Lee, Zhuoran Yang

Using Language to Extend to Unseen Domains

Lisa Dunlap, Clara Mohri, Devin Guillory, Han Zhang, Trevor Darrell

Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization

Jivat Neet Kaur, Emre Kiciman, Amit Sharma

Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts

Zhili Liu, Kai Chen, Jianhua Han, Lanqing Hong, Hang Xu

The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry

Dian Wang, Jung Yeon Park, Neel Sortur, Lawson L.S. Wong, Robin Walters

Towards Interpretable Deep Reinforcement Learning with Human-Friendly Prototypes

Eoin M. Kenny, Mycal Tucker, Julie Shah

Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations

Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson

Provable Defense Against Geometric Transformations

Rem Yang, Jacob Laurel, Sasa Misailovic, Gagandeep Singh

TEMPERA: Test-Time Prompt Editing via Reinforcement Learning

Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez

SMART: Self-supervised Multi-task pretrAining with contRol Transformers

Yanchao Sun, Shuang Ma, Ratnesh Madaan, Rogerio Bonatti, Furong Huang

Associative Memory Augmented Asynchronous Spatiotemporal Representation Learning for Event-based Perception

Uday Kamal, Saurabh Dash, Saibal Mukhopadhyay

DINO as a von Mises-Fisher mixture model

Hariprasath Govindarajan, Per Sidén, Jacob Roll, Fredrik Lindsten

Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation

Lorenz Kuhn, Yarin Gal, Sebastian Farquhar

Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise

Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski

Depth Separation with Multilayer Mean-Field Networks

Yunwei Ren, Mo Zhou, Rong Ge

Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions

Arthur Jacot

Learning rigid dynamics with face interaction graph networks

Kelsey R Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William F Whitney, Alvaro Sanchez-Gonzalez

Disentanglement with Biological Constraints: A Theory of Functional Cell Types

James C. R. Whittington, Will Dorrell, Surya Ganguli, Timothy Behrens

Learning multi-scale local conditional probability models of images

Zahra Kadkhodaie, Florentin Guth, Stephane Mallat, Eero P Simoncelli

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa

Optimal Transport for Offline Imitation Learning

Yicheng Luo, zhengyao jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth

The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks

Daniel Kunin, Atsushi Yamamura, Chao Ma, Surya Ganguli

Contrastive Audio-Visual Masked Autoencoder

Yuan Gong, Andrew Rouditchenko, Alexander H. Liu, David Harwath, Leonid Karlinsky

Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency

Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla

Serving Graph Compression for Graph Neural Networks

Si Si, Felix Yu, Ankit Singh Rawat, Cho-jui Hsieh, Sanjiv Kumar

FedExP: Speeding Up Federated Averaging via Extrapolation

Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi

gDDIM: Generalized denoising diffusion implicit models

Qinsheng Zhang, Molei Tao, Yongxin Chen

Phase2vec: dynamical systems embedding with a physics-informed convolutional network

Matt Ricci, Noa Moriel, Zoe Piran, Mor Nitzan

BC-IRL: Learning Generalizable Reward Functions from Demonstrations

Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier

Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems

Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha

Binding Language Models in Symbolic Languages

Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni

Energy-Inspired Self-Supervised Pretraining for Vision Models

Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu

Real-time variational method for learning neural trajectory and its dynamics

Matthew Dowling, Yuan Zhao, Il Memming Park

Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent

Avrajit Ghosh, He Lyu, Xitong Zhang, Rongrong Wang

Guiding Energy-based Models via Contrastive Latent Variables

Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin

Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning

Huiwon Jang, Hankook Lee, Jinwoo Shin

The In-Sample Softmax for Offline Reinforcement Learning

Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White

SmartFRZ: An Efficient Training Framework using Attention-Based Layer Freezing

Sheng Li, Geng Yuan, Yue Dai, Youtao Zhang, Yanzhi Wang

GEASS: Neural causal feature selection for high-dimensional biological data

Mingze Dong, Yuval Kluger

Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform

Yubei Chen, Zeyu Yun, Yi Ma, Bruno Olshausen, Yann LeCun

Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel

SungYub Kim, Sihwan Park, Kyung-Su Kim, Eunho Yang

On Representing Linear Programs by Graph Neural Networks

Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

Ask Me Anything: A simple strategy for prompting language models

Simran Arora, Avanika Narayan, Mayee F Chen, Laurel Orr, Neel Guha

STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables

Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin

Understanding and Adopting Rational Behavior by Bellman Score Estimation

Kuno Kim, Stefano Ermon

A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning

Xin-Qiang Cai, Yao-Xiang Ding, Zixuan Chen, Yuan Jiang, Masashi Sugiyama

Multi-Objective Online Learning

Jiyan Jiang, Wenpeng Zhang, Shiji Zhou, Lihong Gu, Xiaodong Zeng

Certified Training: Small Boxes are All You Need

Mark Niklas Mueller, Franziska Eckert, Marc Fischer, Martin Vechev

Learning with Logical Constraints but without Shortcut Satisfaction

Zenan Li, Zehua Liu, Yuan Yao, Jingwei Xu, Taolue Chen

Guarded Policy Optimization with Imperfect Online Demonstrations

Zhenghai Xue, Zhenghao Peng, Quanyi Li, Zhihan Liu, Bolei Zhou

Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data

Spencer Frei, Gal Vardi, Peter Bartlett, Nathan Srebro, Wei Hu

Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery

Felix Chalumeau, Raphael Boige, Bryan Lim, Valentin Macé, Maxime Allard

Concept-level Debugging of Part-Prototype Networks

Andrea Bontempelli, Stefano Teso, Katya Tentori, Fausto Giunchiglia, Andrea Passerini

Learning Group Importance using the Differentiable Hypergeometric Distribution

Thomas M. Sutter, Laura Manduchi, Alain Ryser, Julia E Vogt

Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering

Liyao Li, Haobo Wang, Liangyu Zha, Qingyi Huang, Sai Wu

Few-Shot Domain Adaptation For End-to-End Communication

Jayaram Raghuram, Yijing Zeng, Dolores Garcia, Rafael Ruiz, Somesh Jha

Humanly Certifying Superhuman Classifiers

Qiongkai Xu, Christian Walder, Chenchen Xu

Human-Guided Fair Classification for Natural Language Processing

Florian E. Dorner, Momchil Peychev, Nikola Konstantinov, Naman Goel, Elliott Ash

Image as Set of Points

Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun

Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection

Jiajun Fan, Yuzheng Zhuang, Yuecheng Liu, Jianye Hao, Bin Wang

Token Merging: Your ViT But Faster

Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer

Sparse Mixture-of-Experts are Domain Generalizable Learners

Bo Li, Yifei Shen, Jingkang Yang, Yezhen Wang, Jiawei Ren

Rethinking the Expressive Power of GNNs via Graph Biconnectivity

Bohang Zhang, Shengjie Luo, Liwei Wang, Di He

3D generation on ImageNet

Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu, Jian Ren, Hsin-Ying Lee

DaxBench: Benchmarking Deformable Object Manipulation with Differentiable Physics

SIWEI CHEN, Yiqing Xu, Cunjun Yu, Linfeng Li, Xiao Ma

MocoSFL: enabling cross-client collaborative self-supervised learning

Jingtao Li, Lingjuan Lyu, Daisuke Iso, Chaitali Chakrabarti, Michael Spranger

Towards Stable Test-time Adaptation in Dynamic Wild World

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Zhiquan Wen, Yaofo Chen

Win: Weight-Decay-Integrated Nesterov Acceleration for Adaptive Gradient Algorithms

Pan Zhou, Xingyu Xie, Shuicheng Yan

Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization

Haoran Xu, Li Jiang, Jianxiong Li, Zhuoran Yang, Zhaoran Wang

Betty: An Automatic Differentiation Library for Multilevel Optimization

Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric Xing

Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting

Yunhao Zhang, Junchi Yan

AutoGT: Automated Graph Transformer Architecture Search

Zizhao Zhang, Xin Wang, Chaoyu Guan, Ziwei Zhang, Haoyang Li

View Synthesis with Sculpted Neural Points

Yiming Zuo, Jia Deng

Statistical Efficiency of Score Matching: The View from Isoperimetry

Frederic Koehler, Alexander Heckett, Andrej Risteski

Transformers are Sample-Efficient World Models

Vincent Micheli, Eloi Alonso, Francois Fleuret

Tailoring Language Generation Models under Total Variation Distance

Haozhe Ji, Pei Ke, ZHIPENG HU, Rongsheng Zhang, Minlie Huang

Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task

Kenneth Li, Aspen K Hopkins, David Bau, Fernanda Viégas, Hanspeter Pfister