ICLR 2023

1,573 papers

LMSeg: Language-guided Multi-dataset Segmentation

Qiang Zhou, Yuang Liu, Chaohui Yu, Jingliang Li, Zhibin Wang

Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction

Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim

In-sample Actor Critic for Offline Reinforcement Learning

Hongchang Zhang, Yixiu Mao, Boyuan Wang, Shuncheng He, Yi Xu

CircNet: Meshing 3D Point Clouds with Circumcenter Detection

Huan Lei, Ruitao Leng, Liang Zheng, Hongdong Li

Variance-Aware Sparse Linear Bandits

Yan Dai, Ruosong Wang, Simon Shaolei Du

Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots

Wei Hung, Bo Kai Huang, Ping-Chun Hsieh, Xi Liu

Towards Lightweight, Model-Agnostic and Diversity-Aware Active Anomaly Detection

Xu Zhang, Yuan Zhao, Ziang Cui, Liqun Li, Shilin He

Time to augment self-supervised visual representation learning

Arthur Aubret, Markus R. Ernst, Celine Teuliere, Jochen Triesch

Measure the Predictive Heterogeneity

Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang

Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning

Guangyuan SHI, Qimai LI, Wenlong Zhang, JIAXIN CHEN, Xiao-ming Wu

Predictive Inference with Feature Conformal Prediction

Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao

Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models

Kaiyue Wen, Jiaye Teng, Jingzhao Zhang

Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process

Shi Fu, Yunwen Lei, Qiong Cao, Xinmei Tian, Dacheng Tao

Transformer-Patcher: One Mistake Worth One Neuron

Zeyu Huang, Yikang Shen, Xiaofeng Zhang, Jie Zhou, Wenge Rong

Self-supervision through Random Segments with Autoregressive Coding (RandSAC)

Tianyu Hua, Yonglong Tian, Sucheng Ren, Michalis Raptis, Hang Zhao

Generative Modelling with Inverse Heat Dissipation

Severi Rissanen, Markus Heinonen, Arno Solin

Better Generative Replay for Continual Federated Learning

Daiqing Qi, Handong Zhao, Sheng Li

Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning

Zhen Wang, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Huan Sun

Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top

Eduard Gorbunov, Samuel Horváth, Peter Richtarik, Gauthier Gidel

$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks

Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li

A Differential Geometric View and Explainability of GNN on Evolving Graphs

Yazheng Liu, Xi Zhang, Sihong Xie

Distributional Meta-Gradient Reinforcement Learning

Haiyan Yin, Shuicheng Yan, Zhongwen Xu

Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Jonas Landman, Slimane Thabet, Constantin Dalyac, Hela Mhiri, Elham Kashefi

Versatile Neural Processes for Learning Implicit Neural Representations

Zongyu Guo, Cuiling Lan, Zhizheng Zhang, Yan Lu, Zhibo Chen

Simplicial Hopfield networks

Thomas F Burns, Tomoki Fukai

Are More Layers Beneficial to Graph Transformers?

Haiteng Zhao, Shuming Ma, Dongdong Zhang, Zhi-Hong Deng, Furu Wei

Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization

Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking

Yangtian Zhang, Huiyu Cai, Chence Shi, Jian Tang

Semi-supervised learning with a principled likelihood from a generative model of data curation

Stoil Krasimirov Ganev, Laurence Aitchison

A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data

JIAJIN LI, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li

BAYES RISK CTC: CONTROLLABLE CTC ALIGNMENT IN SEQUENCE-TO-SEQUENCE TASKS

Jinchuan Tian, Brian Yan, Jianwei Yu, Chao Weng, Dong Yu

PowerQuant: Automorphism Search for Non-Uniform Quantization

Edouard YVINEC, Arnaud Dapogny, Matthieu Cord, Kevin Bailly

Unsupervised visualization of image datasets using contrastive learning

Niklas Böhm, Philipp Berens, Dmitry Kobak

Video Scene Graph Generation from Single-Frame Weak Supervision

Siqi Chen, Jun Xiao, Long Chen

Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective

Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu

StyleMorph: Disentangled 3D-Aware Image Synthesis with a 3D Morphable StyleGAN

Eric-Tuan Le, Edward Bartrum, Iasonas Kokkinos

MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer

Qihao Zhao, Yangyu Huang, Wei Hu, Fan Zhang, Jun Liu

New Insights for the Stability-Plasticity Dilemma in Online Continual Learning

Dahuin Jung, Dongjin Lee, Sunwon Hong, Hyemi Jang, Ho Bae

Efficient Offline Policy Optimization with a Learned Model

Zichen Liu, Siyi Li, Wee Sun Lee, Shuicheng Yan, Zhongwen Xu

Hyperbolic Self-paced Learning for Self-supervised Skeleton-based Action Representations

Luca Franco, Paolo Mandica, Bharti Munjal, Fabio Galasso

Blurring Diffusion Models

Emiel Hoogeboom, Tim Salimans

How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression?

Jetze Schuurmans, Kim Batselier, Julian Kooij

MultiViz: Towards Visualizing and Understanding Multimodal Models

Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng

Finding the Global Semantic Representation in GAN through Fréchet Mean

Jaewoong Choi, Geonho Hwang, Hyunsoo Cho, Myungjoo Kang

KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP

Yufei Wang, Jiayi Zheng, Can Xu, Xiubo Geng, Tao Shen

Massively Scaling Heteroscedastic Classifiers

Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent

Learning with Auxiliary Activation for Memory-Efficient Training

Sunghyeon Woo, Dongsuk Jeon

Uni-Mol: A Universal 3D Molecular Representation Learning Framework

Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu

Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting

Nicolai Dorka, Tim Welschehold, Wolfram Burgard

On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.

Jianhong Bai, Zuozhu Liu, Hualiang Wang, Jin Hao, Yang Feng

Simple and Scalable Nearest Neighbor Machine Translation

Yuhan Dai, Zhirui Zhang, Qiuzhi Liu, Qu Cui, Weihua Li

Unsupervised Manifold Alignment with Joint Multidimensional Scaling

Dexiong Chen, Bowen Fan, Carlos Oliver, Karsten Borgwardt

Accurate Neural Training with 4-bit Matrix Multiplications at Standard Formats

Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Daniel Soudry

Test-Time Adaptation via Self-Training with Nearest Neighbor Information

Minguk Jang, Sae-Young Chung, Hye Won Chung

Context-enriched molecule representations improve few-shot drug discovery

Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann

Learning to Decompose Visual Features with Latent Textual Prompts

Feng Wang, Manling Li, Xudong Lin, Hairong Lv, Alex Schwing

Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference

Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann

Batch Multivalid Conformal Prediction

Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth

Accelerating Guided Diffusion Sampling with Splitting Numerical Methods

Suttisak Wizadwongsa, Supasorn Suwajanakorn

Improving Out-of-distribution Generalization with Indirection Representations

Kha Pham, Hung Le, Man Ngo, Truyen Tran

Does Deep Learning Learn to Abstract? A Systematic Probing Framework

Shengnan An, Zeqi Lin, Bei Chen, Qiang Fu, Nanning Zheng

Neural Architecture Design and Robustness: A Dataset

Steffen Jung, Jovita Lukasik, Margret Keuper

SpeedyZero: Mastering Atari with Limited Data and Time

Yixuan Mei, Jiaxuan Gao, Weirui Ye, Shaohuai Liu, Yang Gao

Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality

Tom Zahavy, Yannick Schroecker, Feryal Behbahani, Kate Baumli, Sebastian Flennerhag

Memory Gym: Partially Observable Challenges to Memory-Based Agents

Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss

Benchmarking Constraint Inference in Inverse Reinforcement Learning

Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart

ViewCo: Discovering Text-Supervised Segmentation Masks via Multi-View Semantic Consistency

Pengzhen Ren, Changlin Li, Hang Xu, Yi Zhu, Guangrun Wang

Decoupled Training for Long-Tailed Classification With Stochastic Representations

Giung Nam, Sunguk Jang, Juho Lee

A Simple Yet Powerful Deep Active Learning With Snapshots Ensembles

Seohyeon Jung, Sanghyun Kim, Juho Lee

On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning

Yifan Xu, Nicklas Hansen, Zirui Wang, Yung-Chieh Chan, Hao Su

Equivariant Energy-Guided SDE for Inverse Molecular Design

Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li

CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Alignment

Hongwei Xue, Yuchong Sun, Bei Liu, Jianlong Fu, Ruihua Song

Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning

Daniel Palenicek, Michael Lutter, João Carvalho, Jan Peters

Jointly Learning Visual and Auditory Speech Representations from Raw Data

Alexandros Haliassos, Pingchuan Ma, Rodrigo Mira, Stavros Petridis, Maja Pantic

Over-parameterized Model Optimization with Polyak-{\L}ojasiewicz Condition

Yixuan Chen, Yubin Shi, MINGZHI DONG, Xiaochen Yang, Dongsheng Li

TranSpeech: Speech-to-Speech Translation With Bilateral Perturbation

Rongjie Huang, Jinglin Liu, Huadai Liu, Yi Ren, Lichao Zhang

A Neural Mean Embedding Approach for Back-door and Front-door Adjustment

Liyuan Xu, Arthur Gretton

Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection

Martijn Oldenhof, Adam Arany, Yves Moreau, Edward De Brouwer

Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition

Canzhe Zhao, Ruofeng Yang, Baoxiang Wang, Shuai Li

Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks

Namjoon Suh, Tian-Yi Zhou, Xiaoming Huo

Non-parametric Outlier Synthesis

Leitian Tao, Xuefeng Du, Jerry Zhu, Yixuan Li

Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wild

Kaifeng Zhang, Yang Fu, Shubhankar Borse, Hong Cai, Fatih Porikli

Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation

Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock

A Learning Based Hypothesis Test for Harmful Covariate Shift

Tom Ginsberg, Zhongyuan Liang, Rahul G Krishnan

Temporal Coherent Test Time Optimization for Robust Video Classification

Chenyu Yi, Siyuan Yang, Yufei Wang, Haoliang Li, Yap-Peng Tan

MEDICAL IMAGE UNDERSTANDING WITH PRETRAINED VISION LANGUAGE MODELS: A COMPREHENSIVE STUDY

Ziyuan Qin, Huahui Yi, Qicheng Lao, Kang Li

Improving Deep Policy Gradients with Value Function Search

Enrico Marchesini, Christopher Amato

BSTT: A Bayesian Spatial-Temporal Transformer for Sleep Staging

Yuchen Liu, Ziyu Jia

Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model

Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan

Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs

Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan

Mitigating Memorization of Noisy Labels via Regularization between Representations

Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu

Policy Expansion for Bridging Offline-to-Online Reinforcement Learning

Haichao Zhang, Wei Xu, Haonan Yu

DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models

Shansan Gong, Mukai Li, Jiangtao Feng, Zhiyong Wu, Lingpeng Kong

How to prepare your task head for finetuning

Yi Ren, Shangmin Guo, Wonho Bae, Danica J. Sutherland

DiGress: Discrete Denoising diffusion for graph generation

Clément Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher

Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States

Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin

Human alignment of neural network representations

Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith

Prompting GPT-3 To Be Reliable

Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang

Neural Agents Struggle to Take Turns in Bidirectional Emergent Communication

Valentin Taillandier, Dieuwke Hupkes, Benoît Sagot, Emmanuel Dupoux, Paul Michel

Teacher Guided Training: An Efficient Framework for Knowledge Transfer

Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain