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Learning latent jet structure

We summarize our recent work on how to infer on jet formation processes directly from substructure data using generative statistical models. We recount in detail how to cast jet substructure observables’ measurements in terms of Bayesian mixed membership models, in particular Latent Dirichlet Alloca...

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Bibliographic Details
Main Authors: Dillon, Barry M. (Author) , Faroughy, Darius A. (Author) , Kamenik, Jernej F. (Author) , Szewc, Manuel (Author)
Format: Article (Journal)
Language:English
Published: 29 June 2021
In: Symmetry
Year: 2021, Volume: 13, Issue: 7, Pages: 1-11
ISSN:2073-8994
DOI:10.3390/sym13071167
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3390/sym13071167
Verlag, lizenzpflichtig, Volltext: https://www.mdpi.com/2073-8994/13/7/1167
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Author Notes:Barry M. Dillon, Darius A. Faroughy, Jernej F. Kamenik and Manuel Szewc

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