Journal Article

GSI-2023-01107

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Development of machine learning analyses with graph neural network for the WASA-FRS experiment

Ekawa, H. (Corresponding author) ; Dou, W. ; Gao, Y. ; He, Y. ; Kasagi, A. ; Liu, E. ; Muneem, A. ; Nakagawa, M. ; Rappold, C. ; Saito, N. ; Saito, T. R. ; Taki, M. ; Tanaka, Y. K. ; Wang, H. ; Yoshida, J. ; Saito, T.GSI*

2023
Springer Heidelberg

This record in other databases:

Please use a persistent id in citations: doi:10.1140/epja/s10050-023-01016-5

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Contributing Institute(s):

1. FRS / SFRS Experimente (FRS)
2. SuperFRS Experiment Collaboration (SuperFRS-EC@FAIR)

Research Program(s):

1. 612 - Cosmic Matter in the Laboratory (POF4-612) (POF4-612)

Experiment(s):

1. External experiment at external facility/ no experiment at GSI (other)

Appears in the scientific report 2023

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; DEAL Springer ; DEAL Springer ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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