ICLR

On the Importance and Applicability of Pre-Training for Federated Learning

Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han-Wei Shen, Wei-Lun Chao

Comments Accepted to ICLR 2023

Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation

Zengyu Qiu, Xinzhu Ma, Kunlin Yang, Chunya Liu, Jun Hou, Shuai Yi, Wanli Ouyang

Comments ICLR'23 accepted

Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning

Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang

Comments Camera ready version for ICLR 2023

GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Elias Frantar, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh

Comments ICLR 2023

Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-free RL

Ruiquan Huang, Jing Yang, Yingbin Liang

Comments Accepted by ICLR 2023

Emulating radiation transport on cosmological scale using a denoising Unet

Mosima P. Masipa, Sultan Hassan, Mario G. Santos, Gabriella Contardo, Kyunghyun Cho

Comments 5 pages, 4 figures, Accepted at the ICLR 2023 Workshop on Physics for Machine Learning (Camera-ready version)

A Tale of Two Circuits: Grokking as Competition of Sparse and Dense Subnetworks

William Merrill, Nikolaos Tsilivis, Aman Shukla

Comments Published at the Workshop on Understanding Foundation Models at ICLR 2023

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

Zaid Khan, Yun Fu

Comments Accepted to ICLR 2023

QAID: Question Answering Inspired Few-shot Intent Detection

Asaf Yehudai, Matan Vetzler, Yosi Mass, Koren Lazar, Doron Cohen, Boaz Carmeli

Comments ICLR paper

GAMR: A Guided Attention Model for (visual) Reasoning

Mohit Vaishnav, Thomas Serre

Journal ref Eleventh International Conference on Learning Representations (ICLR) 2023

Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems

Yewen Fan, Nian Si, Kun Zhang

Comments Accepted in ICLR 2023

FlexVDW: A machine learning approach to account for protein flexibility in ligand docking

Patricia Suriana, Joseph M. Paggi, Ron O. Dror

Comments Published at the MLDD workshop, International Conference on Learning Representations (ICLR) 2023

Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement

Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang

Comments 19 pages, 11 figures, Published as a conference paper at the International Conference on Learning Representations 2023

A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies

Ada Martin, Valerie Chen, Sérgio Jesus, Pedro Saleiro

Comments 9 pages, 2 figures. Will appear in ICLR 2023's TrustML-(un)Limited workshop

Memorization Capacity of Neural Networks with Conditional Computation

Erdem Koyuncu

Comments To be presented at International Conference on Learning Representations (ICLR), 2023

Imitating Graph-Based Planning with Goal-Conditioned Policies

Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin

Comments Accepted to ICLR 2023

Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs

Yuan Cheng, Ruiquan Huang, Jing Yang, Yingbin Liang

Comments Accepted by ICLR 2023

Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths

Ming Xu, Sourav Garg, Michael Milford, Stephen Gould

Comments ICLR 2023 (Poster)

Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning

Yat Long Lo, Christian Schroeder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson

Comments The 11th International Conference on Learning Representations (ICLR)

Pretrained Vision Models for Predicting High-Risk Breast Cancer Stage

Bonaventure F. P. Dossou, Yenoukoume S. K. Gbenou, Miglanche Ghomsi Nono

Comments Accepted at Machine Learning for Global Health Workshop, ICLR 2023

Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning

Zuhui Wang

Comments Accepted by ICLR 2023 Workshop on TML4H

Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem

Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, Tommi Jaakkola

Comments Appearing in ICLR 2023. Code available: github.com/blt2114/ProtDiff_SMCDiff

Causal Confusion and Reward Misidentification in Preference-Based Reward Learning

Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan, Daniel S. Brown

Comments In the proceedings of the Eleventh International Conference on Learning Representations (ICLR 2023). https://iclr.cc/virtual/2023/poster/10822

Message Passing Neural PDE Solvers

Johannes Brandstetter, Daniel Worrall, Max Welling

Comments Published at ICLR 2022 (Spotlight paper), Github: https://github.com/brandstetter-johannes/MP-Neural-PDE-Solvers

Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL

Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang

Comments In the 10th International Conference on Learning Representations (ICLR 2022)

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

Nicolai Dorka, Tim Welschehold, Wolfram Burgard

Comments ICLR 2023

TypeT5: Seq2seq Type Inference using Static Analysis

Jiayi Wei, Greg Durrett, Isil Dillig

Comments Published as a conference paper at ICLR 2023

InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning

Zhuoran Yu, Yin Li, Yong Jae Lee

Comments Accepted by ICLR 2023

Adaptive Interventions for Global Health: A Case Study of Malaria

África Periáñez, Andrew Trister, Madhav Nekkar, Ana Fernández del Río, Pedro L. Alonso

Comments Accepted for ICLR 2023 Workshop on Machine Learning and Global Health

Eagle: Large-Scale Learning of Turbulent Fluid Dynamics with Mesh Transformers

Steeven Janny, Aurélien Béneteau, Madiha Nadri, Julie Digne, Nicolas Thome, Christian Wolf

Comments Published as a conference paper at ICLR 2023

Journal ref International Conference on Learning Representation (ICLR) 2023