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Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter

dc.contributor.authorAsres, M.W.
dc.contributor.authorOmlin, C.W.
dc.contributor.authorWang, L.
dc.contributor.authorParygin, P.
dc.contributor.authorDittmann, J.
dc.contributor.authorKarapostoli, G.
dc.contributor.authorSeidel, M.
dc.contributor.authorVenditti, R.
dc.contributor.authorLambrecht, L.
dc.contributor.authorUsai, E.
dc.contributor.authorAhmad, M.
dc.contributor.authorFernández Menéndez, Javier 
dc.contributor.authorMaeshima, K.
dc.date.accessioned2024-02-02T07:06:31Z
dc.date.available2024-02-02T07:06:31Z
dc.date.issued2023-12-07
dc.identifier.citationSensors, 23(24) (2023); doi:10.3390/s23249679
dc.identifier.issn1424-8220
dc.identifier.urihttps://hdl.handle.net/10651/71111
dc.description.sponsorshipThe teams at CERN have also received support from the Belgian Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP); SRNSF (Georgia); the Bundesministerium für Bildung und Forschung, the Deutsche Forschungsgemeinschaft (DFG), under Germany’s Excellence Strategy–EXC 2121 “Quantum Universe”—390833306, and under project num- ber 400140256-GRK2497, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the National Research, Development and Innovation Office (NKFIH) (Hungary) under project numbers K 128713, K 143460, and TKP2021-NKTA-64; the Department of Atomic Energy and the Department of Science and Technology, India; the Ministry of Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Korea; the Lithuanian Academy of Sciences; the Scientific and Technical Research Council of Turkey, and Turkish Energy, Nuclear and Mineral Research Agency; the National Academy of Sciences of Ukraine; the US Department of Energy.
dc.language.isoengspa
dc.relation.ispartofSensorsspa
dc.rights© 2023 by the authors.
dc.rightsCC Reconocimiento 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleSpatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeterspa
dc.typejournal articlespa
dc.identifier.doi10.3390/S23249679
dc.relation.publisherversionhttps://doi.org/10.3390/S23249679spa
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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