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Modern Machine Learning and Particle Physics

Forthcoming in April. Now Available: Just Accepted Version

Published onMar 01, 2021
Modern Machine Learning and Particle Physics
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Abstract

Over the past five years, modern machine learning has been quietly revoltionizing particle physics. Old methodology is being outdated and entirely new ways of thinking about data are becoming commonplace. This article will review some aspects of the natural synergy between modern machine learning and particle physics, focusing on applications at the Large Hadron Collider. A sampling of examples is given, from signal/background discrimination tasks using supervised learning to direct data-driven approaches. Some comments on persistent challenges and possible future directions for the field are included at the end.


Just Accepted - Preview

3/1/20: To preview this content, click below for the Just Accepted version of the article. This peer-reviewed version has been accepted for its content and is currently being copyedited to conform with HDSR’s style and formatting requirements.


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