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Deep learning for inferring cause of data anomalies

Daily operation of a large-scale experiment is a resource consuming task, particularly from perspectives of routine data quality monitoring. Typically, data comes from different sub-detectors and the global quality of data depends on the combinatorial performance of each of them. In this paper, the...

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Detalles Bibliográficos
Autores principales:	Azzolini, V., Borisyak, M., Cerminara, G., Derkach, D., Franzoni, G., De Guio, F., Koval, O., Pierini, M., Pol, A., Ratnikov, F., Siroky, F., Ustyuzhanin, A., Vlimant, J-R.
Lenguaje:	eng
Publicado:	2017
Materias:	hep-ex Particle Physics - Experiment cs.LG Computing and Computers physics.data-an Other Fields of Physics
Acceso en línea:	https://dx.doi.org/10.1088/1742-6596/1085/4/042015 http://cds.cern.ch/record/2644811

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