Machine Learning in Top Physics in the ATLAS and CMS Collaborations

Keicher, P.

doi:10.48550/arxiv.2301.09534

2023

DOI: 10.48550/arxiv.2301.09534

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Machine Learning in Top Physics in the ATLAS and CMS Collaborations

P. Keicher¹

Abstract: Machine learning is essential in many aspects of top-quark related physics in the ATLAS and CMS Collaborations. This work aims to give a brief overview over current applications in the two collaborations as well as on-going studies for future applications.

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Machine Learning in Top Physics in the ATLAS and CMS Collaborations

Abstract: Machine learning is essential in many aspects of top-quark related physics in the ATLAS and CMS Collaborations. This work aims to give a brief overview over current applications in the two collaborations as well as on-going studies for future applications.

Cited by 0 publications

References 3 publications

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