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Shared Data and Algorithms for Deep Learning in Fundamental Physics

; ; ; ; ; ; ; ; ; ; ; ;

In
Computing and software for big science 6(1), Seiten/Artikel-Nr.:9

ImpressumCham, Switzerland : Springer International Publishing

Umfang[1]-13

ISSN2510-2036

Online
DOI: 10.1007/s41781-022-00082-6

DOI: 10.18154/RWTH-2022-05195
URL: https://publications.rwth-aachen.de/record/847260/files/847260.pdf

Einrichtungen

  1. Lehr- und Forschungsgebiet Experimentalphysik (Hochenergiephysik) (133320)
  2. Fachgruppe Physik (130000)
  3. III. Physikalisches Institut A (133005)


Thematische Einordnung (Klassifikation)
DDC: 004

OpenAccess:
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Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85129663102
OpenAlex: W3179176799

Interne Identnummern
RWTH-2022-05195
Datensatz-ID: 847260

Beteiligte Länder
Germany

Lizenzstatus der Zeitschrift

 GO


Creative Commons Attribution CC BY 4.0 ; OpenAccess

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Faculty of Mathematics and Natural Sciences (Fac.1) > Department of Physics
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133005
130000
133320

 Record created 2022-05-24, last modified 2026-09-09


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