Autoencoders for unsupervised anomaly detection in high energy physics

A bstract Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for model-independent new physics searches. We scrutinize the usage of autoencoders for unsupervised anomaly detec...

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Bibliographic Details
Published in:	The journal of high energy physics Vol. 2021; no. 6; pp. 1 - 32
Main Authors:	Finke, Thorben, Krämer, Michael, Morandini, Alessandro, Mück, Alexander, Oleksiyuk, Ivan
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021 Springer Nature B.V SpringerOpen
Subjects:	Anomalies Classical and Quantum Gravitation Elementary Particles High energy physics Jets Machine learning Marking Particle physics Physics Physics and Astronomy QCD Phenomenology Quantum chromodynamics Quantum Field Theories Quantum Field Theory Quantum Physics Regular Article - Theoretical Physics Relativity Theory String Theory Jets QCD Phenomenology
ISSN:	1029-8479, 1029-8479
Online Access:	Get full text
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