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@INPROCEEDINGS{Torkian:636471,
      author       = {Torkian, Matin and Nattland, Philipp and Adamowicz, Kai
                      Fabian and Adan, Danyer Perez and Herreros, Daina Leyva
                      Pernia Victor Serrano and Botta, Valeria and Feld, Lutz and
                      Aldaya, Maria},
      title        = {{P}reliminary {S}tudies of tt{H}(bb) {D}ileptonic {E}vents
                      {U}sing {CMS} {R}un3 {D}ata and {I}nitial {T}ests of
                      {SPAN}et in {T}his {C}hannel},
      reportid     = {PUBDB-2025-03685},
      year         = {2025},
      abstract     = {The Standard Model (SM) of particle physics predicts that
                      the Higgs boson couples to fermions via a Yukawa-type
                      interaction, with a strength proportional to the fermion
                      mass. This makes the associated production of a Higgs boson
                      with a top-quark pair ( ttH ) a crucial process to directly
                      probe the top-Higgs Yukawa coupling, an essential parameter
                      for confirming the SM nature of the Higgs boson. Among Higgs
                      boson decays, the channel into a bb quark pair has the
                      largest branching fraction, offering an experimentally
                      promising final state. However, ttH(bb) process faces
                      significant challenges regarding backgrounds, especially tt
                      +jets production, with the ttbb background being irreducible
                      with respect to the ttH, H → bb signal. Advance Machine
                      Learning techniques are essential to improve the sensitivity
                      to the signal process.This work focuses on the analysis of
                      the ttH, H → bb process in events with two leptons, using
                      proton-proton collision data collected by the CMS experiment
                      at the LHC during Run3 at √s = 13.6 TeV . ML methods are
                      explored to significantly enhance the sensitivity to the ttH
                      signal. For the first time in this final state we are
                      exploring the potential of SPANet for jet-parton assignment
                      and neutrino kinematic regressions and finally signal and
                      background classification.},
      month         = {Mar},
      date          = {2025-03-31},
      organization  = {DPG Spring Meeting (German Physical
                       Society), Göttingen (Germany), 31 Mar
                       2025 - 4 Apr 2025},
      cin          = {CMS},
      cid          = {I:(DE-H253)CMS-20120731},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611)},
      pid          = {G:(DE-HGF)POF4-611},
      experiment   = {EXP:(DE-H253)LHC-Exp-CMS-20150101},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://bib-pubdb1.desy.de/record/636471},
}