ICLR 2023

1,573 papers

Long-Tailed Learning Requires Feature Learning

Thomas Laurent, James von Brecht, Xavier Bresson

Learning Human-Compatible Representations for Case-Based Decision Support

Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen

ISAAC Newton: Input-based Approximate Curvature for Newton's Method

Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne

Trading Information between Latents in Hierarchical Variational Autoencoders

Tim Z. Xiao, Robert Bamler

DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images

Bing Wang, Lu Chen, Bo Yang

Novel View Synthesis with Diffusion Models

Daniel Watson, William Chan, Ricardo Martin Brualla, Jonathan Ho, Andrea Tagliasacchi

Asynchronous Gradient Play in Zero-Sum Multi-agent Games

Ruicheng Ao, Shicong Cen, Yuejie Chi

Fooling SHAP with Stealthily Biased Sampling

Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh

Multi-Objective Reinforcement Learning: Convexity, Stationarity and Pareto Optimality

Haoye Lu, Daniel Herman, Yaoliang Yu

Causality Compensated Attention for Contextual Biased Visual Recognition

Ruyang Liu, Jingjia Huang, Thomas H. Li, Ge Li

NANSY++: Unified Voice Synthesis with Neural Analysis and Synthesis

Hyeong-Seok Choi, Jinhyeok Yang, Juheon Lee, Hyeongju Kim

DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases

Donghan Yu, Sheng Zhang, Patrick Ng, Henghui Zhu, Alexander Hanbo Li

ManyDG: Many-domain Generalization for Healthcare Applications

Chaoqi Yang, M Brandon Westover, Jimeng Sun

GAIN: On the Generalization of Instructional Action Understanding

Junlong Li, Guangyi Chen, Yansong Tang, Jinan Bao, Kun Zhang

Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning

Xiangyu Peng, Chen Xing, Prafulla Kumar Choubey, Chien-Sheng Wu, Caiming Xiong

Hybrid RL: Using both offline and online data can make RL efficient

Yuda Song, Yifei Zhou, Ayush Sekhari, Drew Bagnell, Akshay Krishnamurthy

Beyond calibration: estimating the grouping loss of modern neural networks

Alexandre Perez-Lebel, Marine Le Morvan, Gael Varoquaux

Diffusion Probabilistic Fields

Peiye Zhuang, Samira Abnar, Jiatao Gu, Alex Schwing, Joshua M. Susskind

Unicom: Universal and Compact Representation Learning for Image Retrieval

Xiang An, Jiankang Deng, Kaicheng Yang, Jaiwei Li, Ziyong Feng

Transformer Meets Boundary Value Inverse Problems

Ruchi Guo, Shuhao Cao, Long Chen

Distributionally Robust Post-hoc Classifiers under Prior Shifts

Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu

Impossibly Good Experts and How to Follow Them

Aaron Walsman, Muru Zhang, Sanjiban Choudhury, Dieter Fox, Ali Farhadi

AIM: Adapting Image Models for Efficient Video Action Recognition

Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen

Predictor-corrector algorithms for stochastic optimization under gradual distribution shift

Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun

What Can we Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers?

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

Deep Generative Symbolic Regression

Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar

Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective

Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov

SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models

Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, Animesh Garg

FedDAR: Federated Domain-Aware Representation Learning

Aoxiao Zhong, Hao He, Zhaolin Ren, Na Li, Quanzheng Li

Learning differentiable solvers for systems with hard constraints

Geoffrey Negiar, Michael W. Mahoney, Aditi Krishnapriyan

Calibrating Sequence likelihood Improves Conditional Language Generation

Yao Zhao, Mikhail Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh

Understanding new tasks through the lens of training data via exponential tilting

Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules

Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei

Markup-to-Image Diffusion Models with Scheduled Sampling

Yuntian Deng, Noriyuki Kojima, Alexander M Rush

Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation

Maksym Yatsura, Kaspar Sakmann, N. Grace Hua, Matthias Hein, Jan Hendrik Metzen

On the Performance of Temporal Difference Learning With Neural Networks

Haoxing Tian, Ioannis Paschalidis, Alex Olshevsky

Agent-based Graph Neural Networks

Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer

Masked Vision and Language Modeling for Multi-modal Representation Learning

Gukyeong Kwon, Zhaowei Cai, Avinash Ravichandran, Erhan Bas, Rahul Bhotika

Bridge the Inference Gaps of Neural Processes via Expectation Maximization

Qi Wang, Marco Federici, Herke van Hoof

Provable Memorization Capacity of Transformers

Junghwan Kim, Michelle Kim, Barzan Mozafari

Generative Modeling Helps Weak Supervision (and Vice Versa)

Benedikt Boecking, Nicholas Roberts, Willie Neiswanger, Stefano Ermon, Frederic Sala

FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montúfar

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers

Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat

VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis

Angtian Wang, Peng Wang, Jian Sun, Adam Kortylewski, Alan Yuille

Sparse tree-based Initialization for Neural Networks

Patrick Lutz, Ludovic Arnould, Claire Boyer, Erwan Scornet

Constructive TT-representation of the tensors given as index interaction functions with applications

Gleb Ryzhakov, Ivan Oseledets

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola

Meta-Learning in Games

Keegan Harris, Ioannis Anagnostides, Gabriele Farina, Mikhail Khodak, Steven Wu

GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik

Continuous pseudo-labeling from the start

Dan Berrebbi, Ronan Collobert, Samy Bengio, Navdeep Jaitly, Tatiana Likhomanenko

Stable Target Field for Reduced Variance Score Estimation in Diffusion Models

Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola

Average Sensitivity of Decision Tree Learning

Satoshi Hara, Yuichi Yoshida

Dual Diffusion Implicit Bridges for Image-to-Image Translation

Xuan Su, Jiaming Song, Chenlin Meng, Stefano Ermon

Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data

Hitesh Sapkota, Qi Yu

Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions

Ansong Ni, Jeevana Priya Inala, Chenglong Wang, Alex Polozov, Christopher Meek

On the Perils of Cascading Robust Classifiers

Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina Pasareanu

SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency

Junfeng Guo, Yiming Li, Xun Chen, Hanqing Guo, Lichao Sun

Behavior Prior Representation learning for Offline Reinforcement Learning

Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam

RPM: Generalizable Multi-Agent Policies for Multi-Agent Reinforcement Learning

Wei Qiu, Xiao Ma, Bo An, Svetlana Obraztsova, Shuicheng Yan

HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing

Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells

Data Valuation Without Training of a Model

Ki Nohyun, Hoyong Choi, Hye Won Chung

Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning

Chunwei Ma, Zhanghexuan Ji, Ziyun Huang, Yan Shen, Mingchen Gao

Write and Paint: Generative Vision-Language Models are Unified Modal Learners

SHIZHE DIAO, Wangchunshu Zhou, Xinsong Zhang, Jiawei Wang

Distributionally Robust Recourse Action

Duy Nguyen, Ngoc Bui, Viet Anh Nguyen

Spiking Convolutional Neural Networks for Text Classification

Changze Lv, Jianhan Xu, Xiaoqing Zheng

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi

Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting

Zhang-Wei Hong, Pulkit Agrawal, Remi Tachet des Combes, Romain Laroche

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding

Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang

Schema Inference for Interpretable Image Classification

Haofei Zhang, Mengqi Xue, Xiaokang Liu, Kaixuan Chen, Jie Song

Out-of-distribution Representation Learning for Time Series Classification

Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xing Xie

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion

Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian

Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning

Zaid Khan, Yun Fu

ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation

Chiu Wai Yan, Tsz-Him Cheung, Dit-Yan Yeung

Coverage-centric Coreset Selection for High Pruning Rates

Haizhong Zheng, Rui Liu, Fan Lai, Atul Prakash

RGI: robust GAN-inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection

Shancong Mou, Xiaoyi Gu, Meng Cao, Haoping Bai, Ping Huang

Learning Hierarchical Protein Representations via Complete 3D Graph Networks

Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji

NERDS: A General Framework to Train Camera Denoisers from Raw-RGB Noisy Image Pairs

Heewon Kim, Kyoung Mu Lee

Prototypical Calibration for Few-shot Learning of Language Models

Zhixiong Han, Yaru Hao, Li Dong, Yutao Sun, Furu Wei

Hierarchical Sliced Wasserstein Distance

Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Minh Nguyen

SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication

Marco Bornstein, Tahseen Rabbani, Evan Z Wang, Amrit Bedi, Furong Huang

Characterizing the Influence of Graph Elements

Zizhang Chen, Peizhao Li, Hongfu Liu, Pengyu Hong

PV3D: A 3D Generative Model for Portrait Video Generation

Zhongcong XU, Jianfeng Zhang, Jun Hao Liew, Wenqing Zhang, Song Bai

wav2tok: Deep Sequence Tokenizer for Audio Retrieval

Adhiraj Banerjee, Vipul Arora

Boosting Multiagent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks

Jianye Hao, Xiaotian Hao, Hangyu Mao, Weixun Wang, Yaodong Yang

Learned Index with Dynamic ε

Daoyuan Chen, Wuchao Li, Yaliang Li, Bolin Ding, Kai Zeng

Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation

Hongsuk Choi, Hyeongjin Nam, Taeryung Lee, Gyeongsik Moon, Kyoung Mu Lee

MaskFusion: Feature Augmentation for Click-Through Rate Prediction via Input-adaptive Mask Fusion

Chao Liao, Jianchao Tan, Jiyuan Jia, Yi Guo, Chengru Song

Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap

Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf

Latent State Marginalization as a Low-cost Approach for Improving Exploration

Dinghuai Zhang, Aaron Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang

Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation

Yun Young Choi, Sun Woo Park, Youngho Woo, U Jin Choi

Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition

Junyan Wang, Zhenhong Sun, Yichen Qian, Dong Gong, Xiuyu Sun

EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model

Yifu Yuan, Jianye Hao, Fei Ni, Yao Mu, YAN ZHENG

Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks

Sravanti Addepalli, Anshul Nasery, Venkatesh Babu Radhakrishnan, Praneeth Netrapalli, Prateek Jain

Improving Object-centric Learning with Query Optimization

Baoxiong Jia, Yu Liu, Siyuan Huang

Optimal Activation Functions for the Random Features Regression Model

Jianxin Wang, José Bento

Gromov-Wasserstein Autoencoders

Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama

Toward Adversarial Training on Contextualized Language Representation

Hongqiu Wu, Yongxiang Liu, Hanwen Shi, Hai Zhao, Min Zhang

ODAM: Gradient-based Instance-Specific Visual Explanations for Object Detection

Chenyang Zhao, Antoni B. Chan

Treeformer: Dense Gradient Trees for Efficient Attention Computation

Lovish Madaan, Srinadh Bhojanapalli, Himanshu Jain, Prateek Jain

RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data

Sangwoo Mo, Jong-Chyi Su, CHIH-YAO MA, Mido Assran, Ishan Misra