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@INPROCEEDINGS{Farkas:996357,
author = {Farkas, Máté Zoltán and Diekmann, Svenja and Eich,
Niclas and Erdmann, Martin},
collaboration = {{CMS Collaboration}},
title = {{A} method for inferring signal strength modifiers by
conditional invertible neural networks},
volume = {295},
address = {Les Ulis},
publisher = {EDP Sciences},
reportid = {RWTH-2024-10548},
series = {The European physical journal. Web of Conferences},
pages = {09001, [1]-7},
year = {2024},
comment = {26th International Conference on Computing in High Energy
and Nuclear Physics (CHEP 2023) : Norfolk, VA, USA, May
8-12, 2023 / R. De Vita, X. Espinal, P. Laycock and O.
Shadura (eds.)},
booktitle = {26th International Conference on
Computing in High Energy and Nuclear
Physics (CHEP 2023) : Norfolk, VA, USA,
May 8-12, 2023 / R. De Vita, X.
Espinal, P. Laycock and O. Shadura
(eds.)},
month = {May},
date = {2023-05-08},
organization = {26. International Conference on
Computing in High Energy and Nuclear
Physics, Norfolk, VA (USA), 8 May 2023
- 12 May 2023},
cin = {133320 / 130000 / 133005 / 136520},
ddc = {530},
cid = {$I:(DE-82)133320_20140620$ / $I:(DE-82)130000_20140620$ /
$I:(DE-82)133005_20180607$ / $I:(DE-82)136520_20140620$},
typ = {PUB:(DE-HGF)7 / PUB:(DE-HGF)8},
UT = {WOS:001244151902052},
doi = {10.1051/epjconf/202429509001},
url = {https://publications.rwth-aachen.de/record/996357},
}
Gast ::