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Improving ATLAS hadronic object performance with ML/AI Algorithms

Hadronic object reconstruction is one of the most promising settings for cutting-edge machine learning and artificial intelligence algorithms at the LHC. In this contribution, selected highlights of ML/AI applications by ATLAS to particle and boosted-object identification, MET reconstruction and oth...

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Detalles Bibliográficos
Autor principal: Chen, Xiang
Lenguaje:eng
Publicado: 2023
Materias:
Acceso en línea:http://cds.cern.ch/record/2860218

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