Unsupervised and lightly supervised learning in particle physics
We review the main applications of machine learning models that are not fully supervised in particle physics, i.e., clustering, anomaly detection, detector simulation, and unfolding. Unsupervised methods are ideal for anomaly detection tasks—machine learning models can be trained on background data...
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| Published in: | The European physical journal. ST, Special topics Vol. 233; no. 15-16; pp. 2559 - 2596 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.11.2024
Springer Nature B.V |
| Subjects: | |
| ISSN: | 1951-6355, 1951-6401 |
| Online Access: | Get full text |
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