ICLR

DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks

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

Comments ICLR 2023

Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism

Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang

Comments Accepted by ICLR 2023

What Is Missing in IRM Training and Evaluation? Challenges and Solutions

Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush Varshney, Sijia Liu

Comments Accepted to Eleventh International Conference on Learning Representations (ICLR 2023)

Learning Label Encodings for Deep Regression

Deval Shah, Tor M. Aamodt

Comments Published at ICLR 2023 (Notable top-25%)

Journal ref International Conference on Learning Representations 2023 (https://openreview.net/pdf?id=k60XE_b0Ix6)

VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation

Thanh Nguyen-Tang, Raman Arora

Comments top-25%-noble ICLR'23; code: https://github.com/thanhnguyentang/neural-offline-rl; v2: change title

Personalized Reward Learning with Interaction-Grounded Learning (IGL)

Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran, Cheng Tan

Comments ICLR 2023

Learning Hierarchical Protein Representations via Complete 3D Graph Networks

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

Comments The paper has been accepted by ICLR 2023. You can also cite the conference version

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

Tong Yang, Michael I. Jordan, Tatjana Chavdarova

Journal ref International Conference on Learning Representations 2023, Kigali, Rwanda

Few-Shot Domain Adaptation For End-to-End Communication

Jayaram Raghuram, Yijing Zeng, Dolores García Martí, Rafael Ruiz Ortiz, Somesh Jha, Joerg Widmer, Suman Banerjee

Comments 35 pages, Published in ICLR 2023

Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections

Edward De Brouwer, Rahul G. Krishnan

Comments Accepted at ICLR 2023

Journal ref International Conference on Learning Representations (ICLR) 2023

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

Yingda Yin, Yang Wang, He Wang, Baoquan Chen

Comments ICLR 2023 Spotlight (notable-top-25%)

Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning

Rundong Luo, Yifei Wang, Yisen Wang

Comments ICLR 2023

Imitating Human Behaviour with Diffusion Models

Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

Comments Published in ICLR 2023

Journal ref ICLR 2023

Guiding continuous operator learning through Physics-based boundary constraints

Nadim Saad, Gaurav Gupta, Shima Alizadeh, Danielle C. Maddix

Comments Nadim and Gaurav contributed equally in this work. 31 pages, 7 figures, 16 tables

Journal ref ICLR 2023

FairGBM: Gradient Boosting with Fairness Constraints

André F Cruz, Catarina Belém, Sérgio Jesus, João Bravo, Pedro Saleiro, Pedro Bizarro

Comments Published as a conference paper at ICLR 2023

Clifford Neural Layers for PDE Modeling

Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta

Comments Accepted at ICLR-2023

Trainability Preserving Neural Pruning

Huan Wang, Yun Fu

Comments ICLR'23 Camera Ready. 21 Pages. Code: https://github.com/MingSun-Tse/TPP

Verifying the Union of Manifolds Hypothesis for Image Data

Bradley C. A. Brown, Anthony L. Caterini, Brendan Leigh Ross, Jesse C. Cresswell, Gabriel Loaiza-Ganem

Comments ICLR 2023

Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning

Yuandong Tian

Comments ICLR'23 camera ready

Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport

Lingkai Kong, Yuqing Wang, Molei Tao

Comments Code: https://github.com/konglk1203/VariationalStiefelOptimizer

Journal ref ICLR 2023

Deterministic training of generative autoencoders using invertible layers

Gianluigi Silvestri, Daan Roos, Luca Ambrogioni

Comments International Conference on Learning Representations 2023

Computational Language Acquisition with Theory of Mind

Andy Liu, Hao Zhu, Emmy Liu, Yonatan Bisk, Graham Neubig

Comments 9 pages, 3 figures. To be published in the 11th International Conference on Learning Representations, ICLR 2023, Conference Track Proceedings

Image as Set of Points

Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu

Comments ICLR'23 Oral (top 5%); Codes: https://github.com/ma-xu/Context-Cluster

Over-training with Mixup May Hurt Generalization

Zixuan Liu, Ziqiao Wang, Hongyu Guo, Yongyi Mao

Comments Accepted to ICLR 2023

3D generation on ImageNet

Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu, Jian Ren, Hsin-Ying Lee, Peter Wonka, Sergey Tulyakov

Comments ICLR 2023 (Oral)

Journal ref ICLR 2023

DAVA: Disentangling Adversarial Variational Autoencoder

Benjamin Estermann, Roger Wattenhofer

Comments Published as a conference paper at ICLR 2023

Measuring axiomatic soundness of counterfactual image models

Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker

Comments Counterfactual inference, Generative Models, Computer Vision, Published in ICLR 2023

Journal ref The Eleventh International Conference on Learning Representations, ICLR 2023

Iterative Circuit Repair Against Formal Specifications

Matthias Cosler, Frederik Schmitt, Christopher Hahn, Bernd Finkbeiner

Comments To appear at ICLR'23

Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study

Mingxu Tao, Yansong Feng, Dongyan Zhao

Comments Accepted by ICLR 2023. URL: https://openreview.net/forum?id=UazgYBMS9-W

Specformer: Spectral Graph Neural Networks Meet Transformers

Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao

Comments ICLR 2023