Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.
- DOI
- 10.1007/s41781-024-00119-y
- Published
- 2024
- Container
- Computing and software for big science
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s41781-024-00119-y,
title = {Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.},
author = {Angloher G and Banik S and Benato G and Bento A and Bertolini A and Breier R and Bucci C and Burkhart J and Canonica L and D'Addabbo A and Di Lorenzo S and Einfalt L and Erb A and V Feilitzsch F and Fichtinger S and Fuchs D and Garai A and Ghete VM and Gorla P and Guillaumon PV and Gupta S and Hauff D and Ješkovský M and Jochum J and Kaznacheeva M and Kinast A and Kuckuk S and Kluck H and Kraus H and Langenkämper A and Mancuso M and Marini L and Mauri B and Meyer L and Mokina V and Niedermayer K and Olmi M and Ortmann T and Pagliarone C and Pattavina L and Petricca F and Potzel W and Povinec P and Pröbst F and Pucci F and Reindl F and Rothe J and Schäffner K and Schieck J and Schönert S and Schwertner C and Stahlberg M and Stodolsky L and Strandhagen C and Strauss R and Usherov I and Wagner F and Wagner V and Willers M and Zema V and Heitzinger C and Waltenberger W},
year = {2024},
journal = {Computing and software for big science},
doi = {10.1007/s41781-024-00119-y},
url = {https://doi.org/10.1007/s41781-024-00119-y}
}RIS
TY - JOUR TI - Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning. AU - Angloher G AU - Banik S AU - Benato G AU - Bento A AU - Bertolini A AU - Breier R AU - Bucci C AU - Burkhart J AU - Canonica L AU - D'Addabbo A AU - Di Lorenzo S AU - Einfalt L AU - Erb A AU - V Feilitzsch F AU - Fichtinger S AU - Fuchs D AU - Garai A AU - Ghete VM AU - Gorla P AU - Guillaumon PV AU - Gupta S AU - Hauff D AU - Ješkovský M AU - Jochum J AU - Kaznacheeva M AU - Kinast A AU - Kuckuk S AU - Kluck H AU - Kraus H AU - Langenkämper A AU - Mancuso M AU - Marini L AU - Mauri B AU - Meyer L AU - Mokina V AU - Niedermayer K AU - Olmi M AU - Ortmann T AU - Pagliarone C AU - Pattavina L AU - Petricca F AU - Potzel W AU - Povinec P AU - Pröbst F AU - Pucci F AU - Reindl F AU - Rothe J AU - Schäffner K AU - Schieck J AU - Schönert S AU - Schwertner C AU - Stahlberg M AU - Stodolsky L AU - Strandhagen C AU - Strauss R AU - Usherov I AU - Wagner F AU - Wagner V AU - Willers M AU - Zema V AU - Heitzinger C AU - Waltenberger W PY - 2024 JO - Computing and software for big science DO - 10.1007/s41781-024-00119-y UR - https://doi.org/10.1007/s41781-024-00119-y ER -
APA
G, A., S, B., G, B., A, B., A, B., R, B., C, B., J, B., L, C., A, D., S, D. L., L, E., A, E., F, V. F., S, F., D, F., A, G., VM, G., P, G., PV, G., S, G., D, H., M, J., J, J., M, K., A, K., S, K., H, K., H, K., A, L., M, M., L, M., B, M., L, M., V, M., K, N., M, O., T, O., C, P., L, P., F, P., W, P., P, P., F, P., F, P., F, R., J, R., K, S., J, S., S, S., C, S., M, S., L, S., C, S., R, S., I, U., F, W., V, W., M, W., V, Z., C, H., & W, W. (2024). Optimal Operation of Cryogenic Calorimeters Through Deep Reinforcement Learning.. Computing and software for big science. https://doi.org/10.1007/s41781-024-00119-y
Source records
- pubmed · retrieved 2026-09-25T09:28:49.662Z
- europe-pmc · retrieved 2026-09-25T09:28:49.649Z