The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard d...

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Detalles Bibliográficos
Autores principales: Kasieczka, Gregor, Nachman, Benjamin, Shih, David, Amram, Oz, Andreassen, Anders, Benkendorfer, Kees, Bortolato, Blaz, Brooijmans, Gustaaf, Canelli, Florencia, Collins, Jack H., Dai, Biwei, De Freitas, Felipe F., Dillon, Barry M., Dinu, Ioan-Mihail, Dong, Zhongtian, Donini, Julien, Duarte, Javier, Faroughy, D.A., Gonski, Julia, Harris, Philip, Kahn, Alan, Kamenik, Jernej F., Khosa, Charanjit K., Komiske, Patrick, Le Pottier, Luc, Martín-Ramiro, Pablo, Matevc, Andrej, Metodiev, Eric, Mikuni, Vinicius, Murphy, Christopher W., Ochoa, Inês, Park, Sang Eon, Pierini, Maurizio, Rankin, Dylan, Sanz, Veronica, Sarda, Nilai, Seljak, Urŏ, Seljak, Uros, Smolkovic, Aleks, Stein, George, Suarez, Cristina Mantilla, Szewc, Manuel, Thaler, Jesse, Tsan, Steven, Udrescu, Silviu-Marian, Vaslin, Louis, Vlimant, Jean-Roch, Williams, Daniel, Yunus, Mikaeel
Lenguaje:eng
Publicado: 2021
Materias:
physics.data-an
Other Fields of Physics
hep-ex
Particle Physics - Experiment
hep-ph
Particle Physics - Phenomenology
Acceso en línea:https://dx.doi.org/10.1088/1361-6633/ac36b9
http://cds.cern.ch/record/2750642

Internet

https://dx.doi.org/10.1088/1361-6633/ac36b9
http://cds.cern.ch/record/2750642

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