ICLR 2023

1,573 papers

ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks

Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin

Hungry Hungry Hippos: Towards Language Modeling with State Space Models

Daniel Y Fu, Tri Dao, Khaled Kamal Saab, Armin W Thomas, Atri Rudra

MIMT: Masked Image Modeling Transformer for Video Compression

Jinxi Xiang, Kuan Tian, Jun Zhang

LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation

Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren

Ensuring DNN Solution Feasibility for Optimization Problems with Linear Constraints

Tianyu Zhao, Xiang Pan, Minghua Chen, Steven Low

Adversarial Attacks on Adversarial Bandits

Yuzhe Ma, Zhijin Zhou

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning

Zixiang Chen, Chris Junchi Li, Huizhuo Yuan, Quanquan Gu, Michael Jordan

Exploring Temporally Dynamic Data Augmentation for Video Recognition

Taeoh Kim, Jinhyung Kim, Minho Shim, Sangdoo Yun, Myunggu Kang

Semi-Implicit Variational Inference via Score Matching

Longlin Yu, Cheng Zhang

Corrupted Image Modeling for Self-Supervised Visual Pre-Training

Yuxin Fang, Li Dong, Hangbo Bao, Xinggang Wang, Furu Wei

Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images

Jiyeon Han, Hwanil Choi, Yunjey Choi, Junho Kim, Jung-Woo Ha

DiffEdit: Diffusion-based semantic image editing with mask guidance

Guillaume Couairon, Jakob Verbeek, Holger Schwenk, Matthieu Cord

Prompt-to-Prompt Image Editing with Cross-Attention Control

Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch

VA-DepthNet: A Variational Approach to Single Image Depth Prediction

Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Luc Van Gool

Faster Gradient-Free Methods for Escaping Saddle Points

Hualin Zhang, Bin Gu

MARS: Meta-learning as Score Matching in the Function Space

Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause

EA-HAS-Bench: Energy-aware Hyperparameter and Architecture Search Benchmark

Shuguang Dou, XINYANG JIANG, Cai Rong Zhao, Dongsheng Li

The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium

Ian Gemp, Charlie Chen, Brian McWilliams

DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems

Pierre Schumacher, Daniel Haeufle, Dieter Büchler, Syn Schmitt, Georg Martius

On the Usefulness of Embeddings, Clusters and Strings for Text Generation Evaluation

Tiago Pimentel, Clara Isabel Meister, Ryan Cotterell

Martingale Posterior Neural Processes

Hyungi Lee, Eunggu Yun, Giung Nam, Edwin Fong, Juho Lee

Pre-training via Denoising for Molecular Property Prediction

Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh

Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning

Do-Yeon Kim, Dong-Jun Han, Jun Seo, Jaekyun Moon

D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory

Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale

Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Jiahui Gao, Renjie Pi, LIN Yong, Hang Xu, Jiacheng Ye

Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent

Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping

Neural Lagrangian Schr\"{o}dinger Bridge: Diffusion Modeling for Population Dynamics

Takeshi Koshizuka, Issei Sato

DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf

Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection

Shuyang Yu, Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Sparsity-Constrained Optimal Transport

Tianlin Liu, Joan Puigcerver, Mathieu Blondel

Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks

Zhiyuan Cheng, James Chenhao Liang, Guanhong Tao, Dongfang Liu, Xiangyu Zhang

Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers

Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!

Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang

RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch

Yiqin Tan, Pihe Hu, Ling Pan, Jiatai Huang, Longbo Huang

Few-shot Cross-domain Image Generation via Inference-time Latent-code Learning

Arnab Kumar Mondal, Piyush Tiwary, Parag Singla, Prathosh AP

The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks

Blake Bordelon, Cengiz Pehlevan

A Unified Algebraic Perspective on Lipschitz Neural Networks

Alexandre Araujo, Aaron J Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu

STaSy: Score-based Tabular data Synthesis

Jayoung Kim, Chaejeong Lee, Noseong Park

Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning

Onno Eberhard, Jakob Hollenstein, Cristina Pinneri, Georg Martius

ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients

Guihong Li, Yuedong Yang, Kartikeya Bhardwaj, Radu Marculescu

NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning

Ruiqi Ni, Ahmed H Qureshi

Differentially Private L_2-Heavy Hitters in the Sliding Window Model

Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou

Out-of-Distribution Detection and Selective Generation for Conditional Language Models

Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna, Mohammad Saleh

Powderworld: A Platform for Understanding Generalization via Rich Task Distributions

Kevin Frans, Phillip Isola

Quantifying Memorization Across Neural Language Models

Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer

Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask?

Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli

Efficient Discrete Multi Marginal Optimal Transport Regularization

Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh

Neural Design for Genetic Perturbation Experiments

Aldo Pacchiano, Drausin Wulsin, Robert A Barton, Luis Voloch

MEDFAIR: Benchmarking Fairness for Medical Imaging

Yongshuo Zong, Yongxin Yang, Timothy Hospedales

Learning with Stochastic Orders

Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh

Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?

Rui Wen, Zhengyu Zhao, Zhuoran Liu, Michael Backes, Tianhao Wang

Parametrizing Product Shape Manifolds by Composite Networks

Josua Sassen, Klaus Hildebrandt, Martin Rumpf, Benedikt Wirth

Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning

John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael Rabbat

Learning Controllable Adaptive Simulation for Multi-resolution Physics

Tailin Wu, Takashi Maruyama, Qingqing Zhao, Gordon Wetzstein, Jure Leskovec

Hyperbolic Deep Reinforcement Learning

Edoardo Cetin, Benjamin Paul Chamberlain, Michael M. Bronstein, Jonathan J Hunt

Does Zero-Shot Reinforcement Learning Exist?

Ahmed Touati, Jérémy Rapin, Yann Ollivier

Neural Networks Efficiently Learn Low-Dimensional Representations with SGD

Alireza Mousavi-Hosseini, Sejun Park, Manuela Girotti, Ioannis Mitliagkas, Murat A Erdogdu

When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Li Yi, Gezheng Xu, Pengcheng Xu, Jiaqi Li, Ruizhi Pu

Post-hoc Concept Bottleneck Models

Mert Yuksekgonul, Maggie Wang, James Zou

Effects of Graph Convolutions in Multi-layer Networks

Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

A CMDP-within-online framework for Meta-Safe Reinforcement Learning

Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin

Domain Generalization via Heckman-type Selection Models

Hyungu Kahng, Hyungrok Do, Judy Zhong

Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms

Fan Chen, Yu Bai, Song Mei

MeshDiffusion: Score-based Generative 3D Mesh Modeling

Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull

Learning Sparse Group Models Through Boolean Relaxation

Yijie Wang, Yuan Zhou, Xiaoqing Huang, Kun Huang, Jie Zhang

Planning Goals for Exploration

Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman

PiFold: Toward effective and efficient protein inverse folding

Zhangyang Gao, Cheng Tan, Stan Z. Li

Progress measures for grokking via mechanistic interpretability

Neel Nanda, Lawrence Chan, Tom Lieberum, Jess Smith, Jacob Steinhardt

A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation

Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo, Shixiang Shane Gu

DocPrompting: Generating Code by Retrieving the Docs

Shuyan Zhou, Uri Alon, Frank F. Xu, Zhengbao Jiang, Graham Neubig

Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian

Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao

Adversarial Diversity in Hanabi

Brandon Cui, Andrei Lupu, Samuel Sokota, Hengyuan Hu, David J Wu

Re-calibrating Feature Attributions for Model Interpretation

Peiyu Yang, Naveed Akhtar, Zeyi Wen, Mubarak Shah, Ajmal Saeed Mian

ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning

Olga Golovneva, Moya Peng Chen, Spencer Poff, Martin Corredor, Luke Zettlemoyer

CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang

Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer

Eric Qu, Xufang Luo, Dongsheng Li

CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks

Tuomas Oikarinen, Tsui-Wei Weng

PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification

Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula, Ming Lin

Flow Matching for Generative Modeling

Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matthew Le

FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation

Zhou Xian, Bo Zhu, Zhenjia Xu, Hsiao-Yu Tung, Antonio Torralba

Mosaic Representation Learning for Self-supervised Visual Pre-training

Zhaoqing Wang, Ziyu Chen, Yaqian Li, Yandong Guo, Jun Yu

Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models

Xiaoman Pan, Wenlin Yao, Hongming Zhang, Dian Yu, Dong Yu

Minimum Variance Unbiased N:M Sparsity for the Neural Gradients

Brian Chmiel, Itay Hubara, Ron Banner, Daniel Soudry

Symmetric Pruning in Quantum Neural Networks

Xinbiao Wang, Junyu Liu, Tongliang Liu, Yong Luo, Yuxuan Du

Solving Constrained Variational Inequalities via a First-order Interior Point-based Method

Tong Yang, Michael Jordan, Tatjana Chavdarova

Not All Tasks Are Born Equal: Understanding Zero-Shot Generalization

Jing Zhou, Zongyu Lin, Yanan Zheng, Jian Li, Zhilin Yang

Building a Subspace of Policies for Scalable Continual Learning

Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier, Ludovic DENOYER

Decompositional Generation Process for Instance-Dependent Partial Label Learning

Congyu Qiao, Ning Xu, Xin Geng

Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning

Hao He, Kaiwen Zha, Dina Katabi

Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations

Andrii Zadaianchuk, Matthaeus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox

Learning Diffusion Bridges on Constrained Domains

Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu

Inequality phenomenon in l_∞-adversarial training, and its unrealized threats

Ranjie Duan, YueFeng Chen, Yao Zhu, Xiaojun Jia, Rong Zhang

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Xingchao Liu, Chengyue Gong, Qiang Liu

Efficient recurrent architectures through activity sparsity and sparse back-propagation through time

Anand Subramoney, Khaleelulla Khan Nazeer, Mark Schöne, Christian Mayr, David Kappel

Capturing the Motion of Every Joint: 3D Human Pose and Shape Estimation with Independent Tokens

Sen Yang, Wen Heng, Gang Liu, Guozhong Luo, Wankou Yang

Fisher-Legendre (FishLeg) optimization of deep neural networks

Jezabel R Garcia, Federica Freddi, Stathi Fotiadis, Maolin Li, Sattar Vakili

A Primal-Dual Framework for Transformers and Neural Networks

Tan Minh Nguyen, Tam Minh Nguyen, nhật Hồ, Andrea L. Bertozzi, Richard Baraniuk

Dual Algorithmic Reasoning

Danilo Numeroso, Davide Bacciu, Petar Veličković

Training language models to summarize narratives improves brain alignment

Khai Loong Aw, Mariya Toneva

Model-based Causal Bayesian Optimization

Scott Sussex, Anastasia Makarova, Andreas Krause