Eprint already available on another site (E-prints, working papers and research blog)
Deep generative models for fast shower simulation in ATLAS
The ATLAS collaboration; Louppe, Gilles
2018
 

Files


Full Text
ATL-SOFT-PUB-2018-001.pdf
Author preprint (29.34 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Research center :
CERN
Disciplines :
Physics
Computer science
Author, co-author :
The ATLAS collaboration
Other collaborator :
Louppe, Gilles  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Big Data
Language :
English
Title :
Deep generative models for fast shower simulation in ATLAS
Publication date :
12 July 2018
Commentary :
Joint work between Gadatsch, Stefan (Departement de Physique Nucleaire et Corpusculaire, Universite de Geneve) ; Salamani, Dalila (Departement de Physique Nucleaire et Corpusculaire, Universite de Geneve) ; Cranmer, Kyle (Department of Physics, New York University) ; Louppe, Gilles Claude (Department of Physics, New York University) ; Golling, Tobias (Departement de Physique Nucleaire et Corpusculaire, Universite de Geneve) ; Rousseau, David (LAL, Univ. Paris-Sud, IN2P3/CNRS, Universite Paris-Saclay) ; Stewart, Graeme (European Laboratory for Particle Physics, CERN) ; Ghosh, Aishik (LAL, Univ. Paris-Sud, IN2P3/CNRS, Universite Paris-Saclay) for the ATLAS collaboration.
Available on ORBi :
since 13 July 2018

Statistics


Number of views
178 (8 by ULiège)
Number of downloads
100 (1 by ULiège)

Bibliography


Similar publications



Contact ORBi