Autoencoders for unsupervised anomaly detection in high energy physics

Abstract 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 detect...

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Bibliographic Details
Main Authors: Thorben Finke, Michael Krämer, Alessandro Morandini, Alexander Mück, Ivan Oleksiyuk
Format: Article
Language:English
Published: SpringerOpen 2021-06-01
Series:Journal of High Energy Physics
Subjects:
Online Access:https://doi.org/10.1007/JHEP06(2021)161

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