Cargando…
Modern machine learning in the presence of systematic uncertainties for robust and optimized multivariate data analysis in high-energy particle physics
In high energy particle physics, machine learning has already proven to be an indispensable technique to push data analysis to the limits. So far widely accepted and successfully applied in the event reconstruction at the LHC experiments, machine learning is today also increasingly often part of the...
Autor principal: | Wunsch, Stefan |
---|---|
Lenguaje: | eng |
Publicado: |
KIT, Karlsruhe
2021
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2751100 |
Ejemplares similares
-
Multivariate methods for particle identification
por: Visan, Cosmin
Publicado: (2013) -
Jet Energy Scale Uncertainty in ATLAS
por: Robinson, J
Publicado: (2011) -
Jet Energy Scale Uncertainties in ATLAS
por: Barillari, T
Publicado: (2012) -
Jet energy corrections and uncertainties in CMS:
reducing their impact on physics measurements
por: Eusebi, Ricardo
Publicado: (2012) -
On the statistical treatment of LEP beam energy uncertainties
por: Blondel, A
Publicado: (1992)