This chapter gives an overview of the core concepts of machine learning (ML) -- the use of algorithms that learn from data, identify patterns, and make predictions or decisions without being explicitly programmed -- that are relevant to particle physics with some examples of applications to the energy, intensity, cosmic, and accelerator frontiers.
@article{arxiv.2512.11133,
title = {Machine Learning},
author = {Javier M. Duarte and Uros Seljak and Kazu Terao},
journal= {arXiv preprint arXiv:2512.11133},
year = {2025}
}
Comments
Particle Data Group Review of Machine Learning, 2025 update, also available at https://pdg.lbl.gov/2025/reviews/rpp2025-rev-machine-learning.pdf