Improving ATLAS Hadronic Object Performance with ML/AI Algorithms

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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: Hodkinson, Benjamin Haslum
Lenguaje:eng
Publicado: 2023
Materias:
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2863810
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author Hodkinson, Benjamin Haslum
author_facet Hodkinson, Benjamin Haslum
author_sort Hodkinson, Benjamin Haslum
collection CERN
description 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 other tasks are presented.
id cern-2863810
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2023
record_format invenio
spelling cern-28638102023-07-28T04:33:32Zhttp://cds.cern.ch/record/2863810engHodkinson, Benjamin HaslumImproving ATLAS Hadronic Object Performance with ML/AI AlgorithmsParticle Physics - ExperimentHadronic 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 other tasks are presented.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 other tasks are presented.arXiv:2307.01388ATL-PHYS-PROC-2023-028oai:cds.cern.ch:28638102023-07-03
spellingShingle Particle Physics - Experiment
Hodkinson, Benjamin Haslum
Improving ATLAS Hadronic Object Performance with ML/AI Algorithms
title Improving ATLAS Hadronic Object Performance with ML/AI Algorithms
title_full Improving ATLAS Hadronic Object Performance with ML/AI Algorithms
title_fullStr Improving ATLAS Hadronic Object Performance with ML/AI Algorithms
title_full_unstemmed Improving ATLAS Hadronic Object Performance with ML/AI Algorithms
title_short Improving ATLAS Hadronic Object Performance with ML/AI Algorithms
title_sort improving atlas hadronic object performance with ml/ai algorithms
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2863810
work_keys_str_mv AT hodkinsonbenjaminhaslum improvingatlashadronicobjectperformancewithmlaialgorithms

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