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"Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement ..."

G. Angloher et al. (2024)

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DOI: 10.1007/S41781-024-00119-Y

access: open

type: Journal Article

metadata version: 2024-06-25

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  - journals/csbs/AngloherBBBBBBBCDLEEFFFGGGGGHJJKKK24
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G. Angloher, S. Banik, G. Benato, A. Bento, A. Bertolini, R. Breier, C. Bucci, J. Burkhart, L. Canonica, Annarita D'Addabbo, S. Di Lorenzo, L. Einfalt, A. Erb, F. v. Feilitzsch, Stephan Fichtinger, D. Fuchs, A. Garai, V. M. Ghete, P. Gorla, P. V. Guillaumon, S. Gupta, D. Hauff, M. Jeskovský, J. Jochum, M. Kaznacheeva, A. Kinast, S. Kuckuk, H. Kluck, H. Kraus, A. Langenkämper, M. Mancuso, L. Marini, B. Mauri, L. Meyer, V. Mokina, K. Niedermayer, M. Olmi, T. Ortmann, C. Pagliarone, L. Pattavina, F. Petricca, W. Potzel, P. Povinec, F. Pröbst, F. Pucci, F. Reindl, J. Rothe, K. Schäffner, J. Schieck, S. Schönert, C. Schwertner, M. Stahlberg, L. Stodolsky, C. Strandhagen, R. Strauss, I. Usherov, F. Wagner, V. Wagner, M. Willers, V. Zema, C. Heitzinger, Wolfgang Waltenberger:
Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning. Comput. Softw. Big Sci. 8(1): 10 (2024)

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