ICLR 2023

1,573 papers

Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling

Keyu Tian, Yi Jiang, qishuai diao, CHEN LIN, Liwei Wang

Minimax Optimal Kernel Operator Learning via Multilevel Training

Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Bencheng Liao, Shaoyu Chen, Xinggang Wang, Tianheng Cheng, Qian Zhang

IS SYNTHETIC DATA FROM GENERATIVE MODELS READY FOR IMAGE RECOGNITION?

Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano

Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks

Lingshen He, Yuxuan Chen, Zhengyang Shen, Yibo Yang, Zhouchen Lin

Neural Networks and the Chomsky Hierarchy

Grégoire Delétang, Anian Ruoss, Jordi Grau-moya, Tim Genewein, Li Kevin Wenliang

Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning

Yibo Yang, Haobo Yuan, Xiangtai Li, Zhouchen Lin, Philip Torr

STREET: A MULTI-TASK STRUCTURED REASONING AND EXPLANATION BENCHMARK

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henghui Zhu, Rui Dong

ISS: Image as Stepping Stone for Text-Guided 3D Shape Generation

Zhengzhe LIU, Peng Dai, Ruihui Li, Xiaojuan Qi, Chi-Wing Fu

PEER: A Collaborative Language Model

Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis

Generating Diverse Cooperative Agents by Learning Incompatible Policies

Rujikorn Charakorn, Poramate Manoonpong, Nat Dilokthanakul

Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction

Tong Wu, Jiaqi Wang, Xingang Pan, Xudong XU, Christian Theobalt

EVA3D: Compositional 3D Human Generation from 2D Image Collections

Fangzhou Hong, Zhaoxi Chen, Yushi Lan, Liang Pan, Ziwei Liu

No Reason for No Supervision: Improved Generalization in Supervised Models

Mert Bülent Sarıyıldız, Yannis Kalantidis, Karteek Alahari, Diane Larlus

Continuous PDE Dynamics Forecasting with Implicit Neural Representations

Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari

Visual Recognition with Deep Nearest Centroids

Wenguan Wang, Cheng Han, Tianfei Zhou, Dongfang Liu

Human Motion Diffusion Model

Guy Tevet, Sigal Raab, Brian Gordon, Yoni Shafir, Daniel Cohen-or

TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter

Disparate Impact in Differential Privacy from Gradient Misalignment

Maria S. Esipova, Atiyeh Ashari Ghomi, Yaqiao Luo, Jesse C Cresswell

MPCFORMER: FAST, PERFORMANT AND PRIVATE TRANSFORMER INFERENCE WITH MPC

Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric Xing

Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

Yi-Lun Liao, Tess Smidt

GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints

Mohammadsajad Abavisani, David Danks, Sergey Plis

Multi-lingual Evaluation of Code Generation Models

Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Andy Zeng, Maria Attarian, brian ichter, Krzysztof Marcin Choromanski, Adrian Wong

CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations

Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, Yue Chang, G A Pershing

The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning

Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu

Generative Augmented Flow Networks

Ling Pan, Dinghuai Zhang, Aaron Courville, Longbo Huang, Yoshua Bengio

Neuro-Symbolic Procedural Planning with Commonsense Prompting

Yujie Lu, Weixi Feng, Wanrong Zhu, Wenda Xu, Xin Eric Wang

Exploring Active 3D Object Detection from a Generalization Perspective

Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang

Denoising Diffusion Error Correction Codes

Yoni Choukroun, Lior Wolf

Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets

Hayeon Lee, Sohyun An, Minseon Kim, Sung Ju Hwang

LAVA: Data Valuation without Pre-Specified Learning Algorithms

Hoang Anh Just, Feiyang Kang, Tianhao Wang, Yi Zeng, Myeongseob Ko

DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity

Alexander Tyurin, Peter Richtarik

PLOT: Prompt Learning with Optimal Transport for Vision-Language Models

Guangyi Chen, Weiran Yao, Xiangchen Song, Xinyue Li, Yongming Rao

Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors

Jianfei Yang, Xiangyu Peng, Kai Wang, Zheng Zhu, Jiashi Feng

Vision Transformer Adapter for Dense Predictions

Zhe Chen, Yuchen Duan, Wenhai Wang, Junjun He, Tong Lu

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification

Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch

Single-shot General Hyper-parameter Optimization for Federated Learning

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz

Multi-skill Mobile Manipulation for Object Rearrangement

Jiayuan Gu, Devendra Singh Chaplot, Hao Su, Jitendra Malik

Learning Label Encodings for Deep Regression

Deval Shah, Tor M. Aamodt

Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra

Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

Yinhuai Wang, Jiwen Yu, Jian Zhang

Diffusion Models Already Have A Semantic Latent Space

Mingi Kwon, Jaeseok Jeong, Youngjung Uh

The Role of ImageNet Classes in Fréchet Inception Distance

Tuomas Kynkäänniemi, Tero Karras, Miika Aittala, Timo Aila, Jaakko Lehtinen

Neural Episodic Control with State Abstraction

Zhuo Li, Derui Zhu, Yujing Hu, Xiaofei Xie, Lei Ma

Accurate Image Restoration with Attention Retractable Transformer

Jiale Zhang, Yulun Zhang, Jinjin Gu, yongbing zhang, Linghe Kong

Dirichlet-based Uncertainty Calibration for Active Domain Adaptation

Mixue Xie, Shuang Li, Rui Zhang, Chi Harold Liu

Neural Optimal Transport

Alexander Korotin, Daniil Selikhanovych, Evgeny Burnaev

GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation

Chenhongyi Yang, Jiarui Xu, Shalini De Mello, Elliot J. Crowley, Xiaolong Wang

Near-Optimal Adversarial Reinforcement Learning with Switching Costs

Ming Shi, Yingbin Liang, Ness Shroff

Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle

Jae Oh Woo

A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond

LIN Yong, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao

Deterministic training of generative autoencoders using invertible layers

Gianluigi Silvestri, Daan Roos, Luca Ambrogioni

One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks

Shutong Wu, Sizhe Chen, Cihang Xie, Xiaolin Huang

Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation

Zihao Xu, Guang-Yuan Hao, Hao He, Hao Wang

Continual evaluation for lifelong learning: Identifying the stability gap

Matthias De Lange, Gido M van de Ven, Tinne Tuytelaars

Multi-domain image generation and translation with identifiability guarantees

Shaoan Xie, Lingjing Kong, Mingming Gong, Kun Zhang

Hidden Markov Transformer for Simultaneous Machine Translation

Shaolei Zhang, Yang Feng

Packed Ensembles for efficient uncertainty estimation

Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-marc Martinez

Multifactor Sequential Disentanglement via Structured Koopman Autoencoders

Nimrod Berman, Ilan Naiman, Omri Azencot

Formal Mathematics Statement Curriculum Learning

Stanislas Polu, Jesse Michael Han, Kunhao Zheng, Mantas Baksys, Igor Babuschkin

NeRN: Learning Neural Representations for Neural Networks

Maor Ashkenazi, Zohar Rimon, Ron Vainshtein, Shir Levi, Elad Richardson

AANG : Automating Auxiliary Learning

Lucio M. Dery, Paul Michel, Mikhail Khodak, Graham Neubig, Ameet Talwalkar

Unsupervised Model Selection for Time Series Anomaly Detection

Mononito Goswami, Cristian Ignacio Challu, Laurent Callot, Lenon Minorics, Andrey Kan

A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics

Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu

HiViT: A Simpler and More Efficient Design of Hierarchical Vision Transformer

Xiaosong Zhang, Yunjie Tian, Lingxi Xie, Wei Huang, Qi Dai

A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation

Yingda Yin, Yang Wang, He Wang, Baoquan Chen

Outcome-directed Reinforcement Learning by Uncertainty \& Temporal Distance-Aware Curriculum Goal Generation

Daesol Cho, Seungjae Lee, H. Jin Kim

Learning the Positions in CountSketch

Yi Li, Honghao Lin, Simin Liu, Ali Vakilian, David Woodruff

Mass-Editing Memory in a Transformer

Kevin Meng, Arnab Sen Sharma, Alex J Andonian, Yonatan Belinkov, David Bau

Diffusion Posterior Sampling for General Noisy Inverse Problems

Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann, Marc Louis Klasky, Jong Chul Ye

On the complexity of nonsmooth automatic differentiation

Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu

Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective

Yiming Gao, Feiyu Liu, Liang Wang, Zhenjie Lian, Weixuan Wang

QuAnt: Quantum Annealing with Learnt Couplings

Marcel Seelbach Benkner, Maximilian Krahn, Edith Tretschk, Zorah Lähner, Michael Moeller

Toeplitz Neural Network for Sequence Modeling

Zhen Qin, Xiaodong Han, Weixuan Sun, Bowen He, Dong Li

A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning

Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan

SketchKnitter: Vectorized Sketch Generation with Diffusion Models

Qiang Wang, Haoge Deng, Yonggang Qi, Da Li, Yi-Zhe Song

Programmatically Grounded, Compositionally Generalizable Robotic Manipulation

Renhao Wang, Jiayuan Mao, Joy Hsu, Hang Zhao, Jiajun Wu

LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence

Zhihao Shi, Xize Liang, Jie Wang

Continual Unsupervised Disentangling of Self-Organizing Representations

Zhiyuan Li, Xiajun Jiang, Ryan Missel, Prashnna Kumar Gyawali, Nilesh Kumar

Flow Annealed Importance Sampling Bootstrap

Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato

Omnigrok: Grokking Beyond Algorithmic Data

Ziming Liu, Eric J Michaud, Max Tegmark

Code Translation with Compiler Representations

Marc Szafraniec, Baptiste Roziere, Hugh James Leather, Patrick Labatut, Francois Charton

Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting

Xiajun Jiang, Ryan Missel, Zhiyuan Li, Linwei Wang

Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra

Stochastic Multi-Person 3D Motion Forecasting

Sirui Xu, Yu-Xiong Wang, Liangyan Gui

Retrieval-based Controllable Molecule Generation

Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard Baraniuk

A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

Learning to Estimate Shapley Values with Vision Transformers

Ian Connick Covert, Chanwoo Kim, Su-in Lee

CUDA: Curriculum of Data Augmentation for Long-tailed Recognition

Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

Benchmarking Offline Reinforcement Learning on Real-Robot Hardware

Nico Gürtler, Sebastian Blaes, Pavel Kolev, Felix Widmaier, Manuel Wuthrich

UNIFIED-IO: A Unified Model for Vision, Language, and Multi-modal Tasks

Jiasen Lu, Christopher Clark, Rowan Zellers, Roozbeh Mottaghi, Aniruddha Kembhavi

InCoder: A Generative Model for Code Infilling and Synthesis

Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace

Learning to Grow Pretrained Models for Efficient Transformer Training

Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky

Learning Soft Constraints From Constrained Expert Demonstrations

Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart

Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization

Jun-Kun Wang, Andre Wibisono

Combinatorial-Probabilistic Trade-Off: P-Values of Community Properties Test in the Stochastic Block Models

Shuting Shen, Junwei Lu

Distilling Model Failures as Directions in Latent Space

Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry

Relational Attention: Generalizing Transformers for Graph-Structured Tasks

Cameron Diao, Ricky Loynd