Explaining data excesses over the NMSSM parameter space with Deep Learning techniques.

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Title: Explaining data excesses over the NMSSM parameter space with Deep Learning techniques.
Authors: Hammad, A.1 (AUTHOR) hamed@post.kek.jp, Ramos, Raymundo2 (AUTHOR) raramos@kias.re.kr, Chakraborty, Amit3 (AUTHOR) amit.c@srmap.edu.in, Ko, Pyungwon4 (AUTHOR) pko@kias.re.kr, Moretti, Stefano5,6 (AUTHOR) stefano.moretti@cern.ch
Source: Journal of High Energy Physics. Feb2026, Vol. 2026 Issue 2, p1-38. 38p.
Database: Mathematics Source
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+High+Energy+Physics%22">Journal of High Energy Physics</searchLink>. Feb2026, Vol. 2026 Issue 2, p1-38. 38p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=msf&AN=192456454
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/JHEP02(2026)077
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      – Code: eng
        Text: English
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        PageCount: 38
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      – TitleFull: Explaining data excesses over the NMSSM parameter space with Deep Learning techniques.
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            NameFull: Hammad, A.
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            NameFull: Ramos, Raymundo
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            NameFull: Chakraborty, Amit
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            NameFull: Ko, Pyungwon
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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              Value: 2026
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