ICML

Variational Mixture of HyperGenerators for Learning Distributions Over Functions

Batuhan Koyuncu, Pablo Sanchez-Martin, Ignacio Peis, Pablo M. Olmos, Isabel Valera

Comments Accepted at ICML 2023. Camera ready version

Explainable Data-Driven Optimization: From Context to Decision and Back Again

Alexandre Forel, Axel Parmentier, Thibaut Vidal

Comments Authors Accepted Manuscript (AAM), to be published in the Proceedings of the 40th International Conference on Machine Learning, PMLR 202, 2023. Open source code available at https://github.com/alexforel/Explainable-CSO

Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments

Daniel Jarrett, Corentin Tallec, Florent Altché, Thomas Mesnard, Rémi Munos, Michal Valko

Journal ref In Proc. 40th International Conference on Machine Learning (ICML 2023)

Global Optimization with Parametric Function Approximation

Chong Liu, Yu-Xiang Wang

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:22113-22136, 2023

Rethinking Backdoor Attacks

Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry

Comments ICML 2023

A Dual Formulation for Probabilistic Principal Component Analysis

Henri De Plaen, Johan A. K. Suykens

Comments ICML 2023 Workshop on Duality for Modern Machine Learning (DP4ML). 14 pages (8 main + 5 appendix), 4 figures and 4 tables

Scalable Deep Learning for RNA Secondary Structure Prediction

Jörg K. H. Franke, Frederic Runge, Frank Hutter

Comments Accepted at the 2023 ICML Workshop on Computational Biology. Honolulu, Hawaii, USA, 2023

Contextual Reliability: When Different Features Matter in Different Contexts

Gaurav Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan

Comments ICML 2023 Camera Ready Version

Who Needs to Know? Minimal Knowledge for Optimal Coordination

Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael Dennis, Stuart Russell

Comments To be published at ICML 2023

Off-Policy Average Reward Actor-Critic with Deterministic Policy Search

Naman Saxena, Subhojyoti Khastigir, Shishir Kolathaya, Shalabh Bhatnagar

Comments Accepted at ICML 2023

Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation

Wenqing Zheng, S P Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang

Comments Accepted in ICML 2023

Graph Positional Encoding via Random Feature Propagation

Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

Comments ICML 2023

ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction

Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

Comments Accepted by ICML 2023

Sequential Monte Carlo Learning for Time Series Structure Discovery

Feras A. Saad, Brian J. Patton, Matthew D. Hoffman, Rif A. Saurous, Vikash K. Mansinghka

Comments 17 pages, 8 figures, 2 tables. Appearing in ICML 2023

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:29473-29489, 2023

Can Neural Network Memorization Be Localized?

Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang

Comments Accepted at ICML 2023

3D ScatterNet: Inference from 21 cm Light-cones

Xiaosheng Zhao, Shifan Zuo, Yi Mao

Comments 9 pages, 4 figures, 2 tables. Accepted to ICML 2023 Machine Learning for Astrophysics workshop. Comments and suggestions are welcome

Field-Level Inference with Microcanonical Langevin Monte Carlo

Adrian E. Bayer, Uros Seljak, Chirag Modi

Comments Accepted at the ICML 2023 Workshop on Machine Learning for Astrophysics. 4 pages, 4 figures

Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation

Andi Peng, Aviv Netanyahu, Mark Ho, Tianmin Shu, Andreea Bobu, Julie Shah, Pulkit Agrawal

Comments International Conference on Machine Learning (ICML) 2023

Theory of Mind as Intrinsic Motivation for Multi-Agent Reinforcement Learning

Ini Oguntola, Joseph Campbell, Simon Stepputtis, Katia Sycara

Comments To appear at ICML 2023 Workshop on Theory of Mind

Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions

Mahyar Khayatkhoei, Wael AbdAlmageed

Comments To appear in ICML 2023. Updated proof in Appendix B

Multi-class Graph Clustering via Approximated Effective $p$-Resistance

Shota Saito, Mark Herbster

Comments Accepted to ICML2023

Journal ref Proceedings of the 40th International Conference on Machine Learning, 29697--29733, 2023

Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss

Pierre Bréchet, Katerina Papagiannouli, Jing An, Guido Montúfar

Comments 42 pages, 3 figures, accepted at ICML 2023

CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design

Desi R. Ivanova, Joel Jennings, Tom Rainforth, Cheng Zhang, Adam Foster

Comments Proceedings of the 40th International Conference on Machine Learning (ICML 2023); 9 pages, 7 figures

Meta-Learning the Inductive Biases of Simple Neural Circuits

William Dorrell, Maria Yuffa, Peter Latham

Comments 14 pages, 12 figures

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:8389-8402, 2023

The Value of Out-of-Distribution Data

Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein

Comments Previous versions of this work have been presented at the Out-of-Distribution Generalization in Computer Vision (OOD-CV) Workshop (ECCV 2022) and the Workshop on Distribution Shifts (NeurIPS 2022)

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:7366-7389, 2023

PromptCrafter: Crafting Text-to-Image Prompt through Mixed-Initiative Dialogue with LLM

Seungho Baek, Hyerin Im, Jiseung Ryu, Juhyeong Park, Takyeon Lee

Comments 5 pages, AI & HCI Workshop at the 40 International Conference on Machine Learning (ICML) 2023

Evaluating unsupervised disentangled representation learning for genomic discovery and disease risk prediction

Taedong Yun

Comments Accepted to the 2023 ICML Workshop on Computational Biology. Honolulu, Hawaii, USA, 2023

Towards Automated Design of Riboswitches

Frederic Runge, Jörg K. H. Franke, Frank Hutter

Comments 9 pages, Accepted at the 2023 ICML Workshop on Computational Biology

UPSCALE: Unconstrained Channel Pruning

Alvin Wan, Hanxiang Hao, Kaushik Patnaik, Yueyang Xu, Omer Hadad, David Güera, Zhile Ren, Qi Shan

Comments 29 pages, 26 figures, accepted to ICML 2023

A Novel Application of Conditional Normalizing Flows: Stellar Age Inference with Gyrochronology

Phil Van-Lane, Joshua S. Speagle, Stephanie Douglas

Comments Accepted at the ICML 2023 Workshop on Machine Learning for Astrophysics. 10 pages, 3 figures (+1 in appendices)