Modern machine learning and particle physics: an in-depth review

Modern machine learning (ML) techniques are ubiquitous in the field of particle physics. These ML models are primarily meant for exploiting large amounts of high-dimensional data to reduce complexity and extract as much information as possible from data. This special issue presents a series of ten c...

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Bibliographic Details
Published in:	The European physical journal. ST, Special topics Vol. 233; no. 15-16; pp. 2421 - 2424
Main Authors:	Bhattacherjee, Biplob, Mukherjee, Swagata
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2024 Springer Nature B.V
Subjects:	Algorithms Atomic Classical and Continuum Physics Condensed Matter Physics Decision trees Editorial Experiments Machine learning Materials Science Measurement Science and Instrumentation Modern Machine Learning and Particle Physics: An In-Depth Review Molecular Neural networks Optical and Plasma Physics Particle physics Physics Physics and Astronomy Quarks Sensors Simulation
ISSN:	1951-6355, 1951-6401
Online Access:	Get full text
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