ICLR 2023

1,573 papers

Conditional Antibody Design as 3D Equivariant Graph Translation

Xiangzhe Kong, Wenbing Huang, Yang Liu

Near-optimal Policy Identification in Active Reinforcement Learning

Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger

Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve

Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa

The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillation

Zihui Xue, Zhengqi Gao, Sucheng Ren, Hang Zhao

Visual Classification via Description from Large Language Models

Sachit Menon, Carl Vondrick

From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data

Zichen Jeff Cui, Yibin Wang, Nur Muhammad Mahi Shafiullah, Lerrel Pinto

Personalized Federated Learning with Feature Alignment and Classifier Collaboration

Jian Xu, Xinyi Tong, Shao-Lun Huang

MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting

Huiqiang Wang, Jian Peng, Feihu Huang, Jince Wang, Junhui Chen

Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction

David Klee, Ondrej Biza, Robert Platt, Robin Walters

Graph Neural Networks for Link Prediction with Subgraph Sketching

Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich

Clean-image Backdoor: Attacking Multi-label Models with Poisoned Labels Only

Kangjie Chen, Xiaoxuan Lou, Guowen Xu, Jiwei Li, Tianwei Zhang

Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search

Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun

Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation

Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber

Language Modelling with Pixels

Phillip Rust, Jonas F. Lotz, Emanuele Bugliarello, Elizabeth Salesky, Miryam de Lhoneux

Relative representations enable zero-shot latent space communication

Luca Moschella, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello

Towards Open Temporal Graph Neural Networks

Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search

Michał Zawalski, Michał Tyrolski, Konrad Czechowski, Tomasz Odrzygóźdź, Damian Stachura

A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification

Paul F Jaeger, Carsten Tim Lüth, Lukas Klein, Till J. Bungert

Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement

Chongyi Li, Chun-Le Guo, man zhou, Zhexin Liang, Shangchen Zhou

REVISITING PRUNING AT INITIALIZATION THROUGH THE LENS OF RAMANUJAN GRAPH

Duc N.M Hoang, Shiwei Liu, Radu Marculescu, Zhangyang Wang

Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs

Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothee Lacroix, Jiacheng Liu

Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks

Guangji Bai, Chen Ling, Liang Zhao

Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

Shuaichen Chang, Jun Wang, Mingwen Dong, Lin Pan, Henghui Zhu

Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier

Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G Bellemare

PaLI: A Jointly-Scaled Multilingual Language-Image Model

Xi Chen, Xiao Wang, Soravit Changpinyo, AJ Piergiovanni, Piotr Padlewski

SimPer: Simple Self-Supervised Learning of Periodic Targets

Yuzhe Yang, Xin Liu, Jiang Wu, Silviu Borac, Dina Katabi

Moving Forward by Moving Backward: Embedding Action Impact over Action Semantics

Kuo-Hao Zeng, Luca Weihs, Roozbeh Mottaghi, Ali Farhadi

Simplified State Space Layers for Sequence Modeling

Jimmy T.H. Smith, Andrew Warrington, Scott Linderman

Efficiently Computing Nash Equilibria in Adversarial Team Markov Games

Fivos Kalogiannis, Ioannis Anagnostides, Ioannis Panageas, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Vaggos Chatziafratis

Extreme Q-Learning: MaxEnt RL without Entropy

Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon

Learning on Large-scale Text-attributed Graphs via Variational Inference

Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu

SAM as an Optimal Relaxation of Bayes

Thomas Möllenhoff, Mohammad Emtiyaz Khan

Efficient Attention via Control Variates

Lin Zheng, Jianbo Yuan, Chong Wang, Lingpeng Kong

Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning

Anton Bakhtin, David J Wu, Adam Lerer, Jonathan Gray, Athul Paul Jacob

Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives

Shaokun Zhang, Feiran Jia, Chi Wang, Qingyun Wu

Near-optimal Coresets for Robust Clustering

Lingxiao Huang, Shaofeng H.-C. Jiang, Jianing Lou, Xuan Wu

Confidential-PROFITT: Confidential PROof of FaIr Training of Trees

Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs

Compressing multidimensional weather and climate data into neural networks

Langwen Huang, Torsten Hoefler

Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning

Antonia Creswell, Murray Shanahan, Irina Higgins

In-context Reinforcement Learning with Algorithm Distillation

Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer

Transformers Learn Shortcuts to Automata

Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness

Joel Dapello, Kohitij Kar, Martin Schrimpf, Robert Baldwin Geary, Michael Ferguson

Efficient Conditionally Invariant Representation Learning

Roman Pogodin, Namrata Deka, Yazhe Li, Danica J. Sutherland, Victor Veitch

Agree to Disagree: Diversity through Disagreement for Better Transferability

Matteo Pagliardini, Martin Jaggi, Francois Fleuret, Sai Praneeth Karimireddy

The Lie Derivative for Measuring Learned Equivariance

Nate Gruver, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson

Is Conditional Generative Modeling all you need for Decision Making?

Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola

Do We Really Need Complicated Model Architectures For Temporal Networks?

Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu

ReAct: Synergizing Reasoning and Acting in Language Models

Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach

Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan

Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching

Donggyun Kim, Jinwoo Kim, Seongwoong Cho, Chong Luo, Seunghoon Hong

Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil SALIM

DreamFusion: Text-to-3D using 2D Diffusion

Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall

On the duality between contrastive and non-contrastive self-supervised learning

Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun

Learning where and when to reason in neuro-symbolic inference

Cristina Cornelio, Jan Stuehmer, Shell Xu Hu, Timothy Hospedales

Dichotomy of Control: Separating What You Can Control from What You Cannot

Sherry Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection

Jinhyung Park, Chenfeng Xu, Shijia Yang, Kurt Keutzer, Kris M. Kitani

On the Sensitivity of Reward Inference to Misspecified Human Models

Joey Hong, Kush Bhatia, Anca Dragan

Confidence-Conditioned Value Functions for Offline Reinforcement Learning

Joey Hong, Aviral Kumar, Sergey Levine

When and Why Vision-Language Models Behave like Bags-Of-Words, and What to Do About It?

Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, James Zou

Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning

Zeyuan Allen-Zhu, Yuanzhi Li

What learning algorithm is in-context learning? Investigations with linear models

Ekin Akyürek, Dale Schuurmans, Jacob Andreas, Tengyu Ma, Denny Zhou

Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes

Aviral Kumar, Rishabh Agarwal, XINYANG GENG, George Tucker, Sergey Levine

Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification

Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama

The Role of Coverage in Online Reinforcement Learning

Tengyang Xie, Dylan J Foster, Yu Bai, Nan Jiang, Sham M. Kakade

Git Re-Basin: Merging Models modulo Permutation Symmetries

Samuel Ainsworth, Jonathan Hayase, Siddhartha Srinivasa

WikiWhy: Answering and Explaining Cause-and-Effect Questions

Matthew Ho, Aditya Sharma, Justin Chang, Michael Saxon, Sharon Levy

A Kernel Perspective of Skip Connections in Convolutional Networks

Daniel Barzilai, Amnon Geifman, Meirav Galun, Ronen Basri

Scaling Up Probabilistic Circuits by Latent Variable Distillation

Anji Liu, Honghua Zhang, Guy Van den Broeck

Transfer NAS with Meta-learned Bayesian Surrogates

Gresa Shala, Thomas Elsken, Frank Hutter, Josif Grabocka

Modeling content creator incentives on algorithm-curated platforms

Jiri Hron, Karl Krauth, Michael Jordan, Niki Kilbertus, Sarah Dean

Encoding Recurrence into Transformers

Feiqing Huang, Kexin Lu, Yuxi CAI, Zhen Qin, Yanwen Fang

Continuous-Discrete Convolution for Geometry-Sequence Modeling in Proteins

Hehe Fan, Zhangyang Wang, Yi Yang, Mohan Kankanhalli

Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning

Shaofeng Zhang, Feng Zhu, Rui Zhao, Junchi Yan

Contextual Image Masking Modeling via Synergized Contrasting without View Augmentation for Faster and Better Visual Pretraining

Shaofeng Zhang, Feng Zhu, Rui Zhao, Junchi Yan

DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks

Wenqian Li, Yinchuan Li, Zhigang Li, Jianye Hao, Yan Pang

Delving into Semantic Scale Imbalance

Yanbiao Ma, Licheng Jiao, Fang Liu, Yuxin Li, Shuyuan Yang

The Augmented Image Prior: Distilling 1000 Classes by Extrapolating from a Single Image

Yuki M Asano, Aaqib Saeed

SIMPLE: Specialized Model-Sample Matching for Domain Generalization

Ziyue Li, Kan Ren, XINYANG JIANG, Yifei Shen, Haipeng Zhang

Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching

Shengchao Liu, Hongyu Guo, Jian Tang

DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Manipulation

Yan Zhao, Ruihai Wu, Zhehuan Chen, Yourong Zhang, Qingnan Fan

On amortizing convex conjugates for optimal transport

Brandon Amos

Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement

Yoonho Lee, Huaxiu Yao, Chelsea Finn

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Yoonho Lee, Annie S Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao

Representation Learning for Low-rank General-sum Markov Games

Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Zihan Ding, Chi Jin

Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

Guoyang Xie, Jinbao Wang, Jiaqi Liu, Yaochu Jin, Feng Zheng

H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection

Xue Yang, Gefan Zhang, Wentong Li, Yue Zhou, Xuehui Wang

Achieve the Minimum Width of Neural Networks for Universal Approximation

Yongqiang Cai

Suppressing the Heterogeneity: A Strong Feature Extractor for Few-shot Segmentation

Zhengdong Hu, Yifan Sun, Yi Yang

A Multi-Grained Self-Interpretable Symbolic-Neural Model For Single/Multi-Labeled Text Classification

Xiang Hu, XinYu KONG, Kewei Tu

BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection

Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinhong Jiang

Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong

Learning Domain-Agnostic Representation for Disease Diagnosis

Churan Wang, Jing Li, Xinwei Sun, Fandong Zhang, Yizhou Yu

TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding

Hanrong Ye, Dan Xu

A Unified Framework for Soft Threshold Pruning

Yanqi Chen, Zhengyu Ma, Wei Fang, Xiawu Zheng, Zhaofei Yu

DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training

Joya Chen, Kai Xu, Yuhui Wang, Yifei Cheng, Angela Yao

Harnessing Out-Of-Distribution Examples via Augmenting Content and Style

Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong

Diagnosing and Rectifying Vision Models using Language

Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou

Trainability Preserving Neural Pruning

Huan Wang, Yun Fu

IDEAL: Query-Efficient Data-Free Learning from Black-Box Models

Jie Zhang, Chen Chen, Lingjuan Lyu

Decompose to Generalize: Species-Generalized Animal Pose Estimation

Guangrui Li, Yifan Sun, Zongxin Yang, Yi Yang