Aspen Open Jets: unlocking LHC data for foundation models in particle physics

Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrates how data collected by the CMS experiment at the Large Hadron Collider can be useful in pre-training foundation models...

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Autors principals:	Oz Amram, Luca Anzalone, Joschka Birk, Darius A Faroughy, Anna Hallin, Gregor Kasieczka, Michael Krämer, Ian Pang, Humberto Reyes-Gonzalez, David Shih
Format:	Artigo
Idioma:	Inglês
Publicat:	IOP Publishing 2025-01-01
Col·lecció:	Machine Learning: Science and Technology
Matèries:	foundation models particle physics transfer learning generation jet physics transformer
Accés en línia:	https://doi.org/10.1088/2632-2153/ade58f
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