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

Open source

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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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

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