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

1 code implementation • 16 May 2021 • 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

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 new ones.

Jet Flavour Classification Using DeepJet

no code implementations • 24 Aug 2020 • Emil Bols, Jan Kieseler, Mauro Verzetti, Markus Stoye, Anna Stakia

Jet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC.

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