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Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance

Autoencoders have useful applications in high energy physics in anomaly detection, particularly for jets - collimated showers of particles produced in collisions such as those at the CERN Large Hadron Collider. We explore the use of graph-based autoencoders, which operate on jets in their "part...

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Detalles Bibliográficos
Autores principales:	Tsan, Steven, Kansal, Raghav, Aportela, Anthony, Diaz, Daniel, Duarte, Javier, Krishna, Sukanya, Mokhtar, Farouk, Vlimant, Jean-Roch, Pierini, Maurizio
Lenguaje:	eng
Publicado:	2021
Materias:	hep-ex Particle Physics - Experiment cs.LG Computing and Computers physics.data-an Other Fields of Physics
Acceso en línea:	http://cds.cern.ch/record/2791648

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