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Abdughani, Murat, Ren, Jie, Wu, Lei, Yang, Jin Min (2019) Probing stop pair production at the LHC with graph neural networks. Journal of High Energy Physics, 2019. doi:10.1007/jhep08(2019)055

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Reference TypeJournal (article/letter/editorial)
TitleProbing stop pair production at the LHC with graph neural networks
JournalJournal of High Energy Physics
AuthorsAbdughani, MuratAuthor
Ren, JieAuthor
Wu, LeiAuthor
Yang, Jin MinAuthor
Year2019 (August)Volume2019
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/jhep08(2019)055Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID12372557Long-form Identifiermindat:1:5:12372557:0
GUID0
Full ReferenceAbdughani, Murat, Ren, Jie, Wu, Lei, Yang, Jin Min (2019) Probing stop pair production at the LHC with graph neural networks. Journal of High Energy Physics, 2019. doi:10.1007/jhep08(2019)055
Plain TextAbdughani, Murat, Ren, Jie, Wu, Lei, Yang, Jin Min (2019) Probing stop pair production at the LHC with graph neural networks. Journal of High Energy Physics, 2019. doi:10.1007/jhep08(2019)055
In(n.d.) Journal of High Energy Physics Vol. 2019. Springer Science and Business Media LLC

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Cao, Junjie, Han, Chengcheng, Wu, Lei, Yang, Jin Min, Zhang, Yang (2012) Probing natural SUSY from stop pair production at the LHC. Journal of High Energy Physics, 2012. doi:10.1007/jhep11(2012)039
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Bandyopadhyay, Priyotosh, Chun, Eung Jin, Mandal, Rusa (2019) Phenomenology of Higgs bosons in inverse seesaw model with Type-X two Higgs doublet at the LHC. Journal of High Energy Physics, 2019. doi:10.1007/jhep08(2019)169
Catani, Stefano, Devoto, Simone, Grazzini, Massimiliano, Kallweit, Stefan, Mazzitelli, Javier (2019) Top-quark pair production at the LHC: fully differential QCD predictions at NNLO. Journal of High Energy Physics, 2019. doi:10.1007/jhep07(2019)100
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Ren, Jie, Wu, Lei, Yang, Jin Min, Zhao, Jun (2019) Exploring supersymmetry with machine learning. Nuclear Physics B, 943. 114613pp. doi:10.1016/j.nuclphysb.2019.114613
 
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