TrackML : a tracking Machine Learning challenge

The High-Luminosity LHC will see pileup levels reaching 200, which will greatly increase the complexity of the tracking component of the event reconstruction. To reach out to Computer Science specialists, a Tracking Machine Learning challenge (TrackML) was set up on Kaggle in 2018 by a team of ATLAS...

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Detalles Bibliográficos
Autores principales: Golling, Tobias, Amrouche, Sabrina, Kiehn, Moritz, Calafiura, Paolo, Farrell, Steven, Gray, Heather M, Estrade, Victor, Germain, Cécile, Gligorov, Vava, Guyon, Isabelle, Hushchyn, Mikhail, Ustyuzhanin, Andrey, Innocente, Vincenzo, Salzburger, Andreas, Moyse, Edward, Rousseau, David, Yilmaz, Yetkin, Vlimant, Jean-Roch
Lenguaje:eng
Publicado: SISSA 2019
Materias:
Particle Physics - Experiment
Computing and Computers
Acceso en línea:https://dx.doi.org/10.22323/1.340.0159
http://cds.cern.ch/record/2704180

Internet

https://dx.doi.org/10.22323/1.340.0159
http://cds.cern.ch/record/2704180

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