Supervised Deep Learning in High Energy Phenomenology: a Mini Review*
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Publication:3387794
DOI10.1088/0253-6102/71/8/955zbMath1452.68168arXiv1905.06047OpenAlexW2969688067MaRDI QIDQ3387794
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Publication date: 13 January 2021
Published in: Communications in Theoretical Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1905.06047
Artificial neural networks and deep learning (68T07) Other elementary particle theory in quantum theory (81V25)
Related Items (5)
Probing single stop production at the FCC-hh/SPPC ⋮ Enhanced Higgs pair production from Higgsino decay at the HL-LHC ⋮ Search for pair-produced vectorlike lepton singlet at the ILC by the XGBoost method ⋮ Mono-\(b\) events from single stop production at the HL-LHC and HE-LHC ⋮ Collider physics at the precision frontier
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