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The DNNLikelihood: enhancing likelihood distribution with Deep Learning

We introduce the DNNLikelihood, a novel framework to easily encode, through deep neural networks (DNN), the full experimental information contained in complicated likelihood functions (LFs). We show how to efficiently parametrise the LF, treated as a multivariate function of parameters of interest a...

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Detalles Bibliográficos
Autores principales:	Coccaro, Andrea, Pierini, Maurizio, Silvestrini, Luca, Torre, Riccardo
Lenguaje:	eng
Publicado:	2019
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/10.1140/epjc/s10052-020-8230-1 http://cds.cern.ch/record/2700228

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