Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider

Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider

Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named “AMVA4NewPhysics” studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely ne...

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Autores principales: Anna Stakia, Tommaso Dorigo, Giovanni Banelli, Daniela Bortoletto, Alessandro Casa, Pablo de Castro, Christophe Delaere, Julien Donini, Livio Finos, Michele Gallinaro, Andrea Giammanco, Alexander Held, Fabricio Jiménez Morales, Grzegorz Kotkowski, Seng Pei Liew, Fabio Maltoni, Giovanna Menardi, Ioanna Papavergou, Alessia Saggio, Bruno Scarpa, Giles C. Strong, Cecilia Tosciri, João Varela, Pietro Vischia, Andreas Weiler
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
Materias:
Particle physics
CERN LHC
CMS
ATLAS
AMVA4NewPhysics
Machine learning
Physics
QC1-999
Acceso en línea:https://doaj.org/article/25b70fead16849348ede3777110406cd
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