Learning the latent structure of collider events
Abstract We describe a technique to learn the underlying structure of collider events directly from the data, without having a particular theoretical model in mind. It allows to infer aspects of the theoretical model that may have given rise to this structure, and can be used to cluster or classify...
Main Authors: | B. M. Dillon, D. A. Faroughy, J. F. Kamenik, M. Szewc |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2020-10-01
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Series: | Journal of High Energy Physics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1007/JHEP10(2020)206 |
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