iml-wg/HEPML-LivingReview
Living Review of Machine Learning for Particle Physics
This document helps particle physicists stay current with the rapidly evolving field of machine learning applications in high-energy physics. It provides a frequently updated, curated list of research papers and reviews, organized by topic. This resource is for researchers, experimentalists, and theorists in particle physics looking to apply or develop modern machine learning techniques in their analyses.
423 stars.
Use this if you are a particle physicist who needs a comprehensive and up-to-date bibliography of machine learning research relevant to your field.
Not ideal if you are looking for introductory materials on machine learning fundamentals or a guide on how to implement specific machine learning algorithms.
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Last pushed
Mar 02, 2026
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