An open-source machine learning framework for global analyses of parton distributions

10.1140/epjc/s10052-021-09747-9

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Bibliographic Details
Main Authors: Ball, Richard D., Carrazza, Stefano, Cruz-Martinez, Juan, Del Debbio, Luigi, Forte, Stefano, Giani, Tommaso, Iranipour, Shayan, Kassabov, Zahari, Latorre, Jose, I, Nocera, Emanuele R., Pearson, Rosalyn L., Rojo, Juan, Stegeman, Roy, Schwan, Christopher, Ubiali, Maria, Voisey, Cameron, Wilson, Michael
Other Authors: PHYSICS
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2022
Online Access:https://scholarbank.nus.edu.sg/handle/10635/232387
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Institution: National University of Singapore
Description
Summary:10.1140/epjc/s10052-021-09747-9