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Modern Machine Learning and Particle Physics

1 Pith paper cite this work. Polarity classification is still indexing.

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abstract

Over the past five years, modern machine learning has been quietly revolutionizing 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 Old methodology is being outdated and entirely new ways of thinking about data are becoming commonplace.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.

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representative citing papers

Jet Image Tagging Using Deep Learning: An Ensemble Model

physics.data-an · 2025-08-09 · conditional · novelty 4.0

An ensemble of ResNet50 and InceptionV3 convolutional networks classifies JetNet jet images with about 75% multi-class accuracy, slightly better than each network alone.

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  • Jet Image Tagging Using Deep Learning: An Ensemble Model physics.data-an · 2025-08-09 · conditional · none · ref 7 · internal anchor

    An ensemble of ResNet50 and InceptionV3 convolutional networks classifies JetNet jet images with about 75% multi-class accuracy, slightly better than each network alone.