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                                       Details for article 16 of 39 found articles
 
 
  Experimental data-driven modeling and prediction of (γ,n) cross-sections with physics-informed neural networks and gradient boosted decision trees
 
 
Title: Experimental data-driven modeling and prediction of (γ,n) cross-sections with physics-informed neural networks and gradient boosted decision trees
Author: Besnard-Vauterin, C.
Besnard, Q.
Blideanu, V.
Khouri, K.Al
Bony, M.
Appeared in: Nuclear instruments and methods in physics research. Section B, Beam interactions with materials and atoms
Paging: Volume 566 () nr. C pages p.
Year: 2025
Contents:
Publisher: Elsevier B.V.
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 16 of 39 found articles
 
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 Koninklijke Bibliotheek - National Library of the Netherlands