Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.
Angloher G, Banik S, Benato G, Bento A, Bertolini A, Breier R, Bucci C, Burkhart J, Canonica L, D'Addabbo A, Di Lorenzo S, Einfalt L, Erb A, V Feilitzsch F, Fichtinger S, Fuchs D, Garai A, Ghete VM, Gorla P, Guillaumon PV, Gupta S, Hauff D, Ješkovský M, Jochum J, Kaznacheeva M, Kinast A, Kuckuk S, Kluck H, Kraus H, Langenkämper A, Mancuso M, Marini L, Mauri B, Meyer L, Mokina V, Niedermayer K, Olmi M, Ortmann T, Pagliarone C, Pattavina L, Petricca F, Potzel W, Povinec P, Pröbst F, Pucci F, Reindl F, Rothe J, Schäffner K, Schieck J, Schönert S, Schwertner C, Stahlberg M, Stodolsky L, Strandhagen C, Strauss R, Usherov I, Wagner F, Wagner V, Willers M, Zema V, Heitzinger C, Waltenberger W.
Angloher G, et al. Among authors: fuchs d.
Comput Softw Big Sci. 2024;8(1):10. doi: 10.1007/s41781-024-00119-y. Epub 2024 May 22.
Comput Softw Big Sci. 2024.
PMID: 39539389
Free PMC article.
