% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@INPROCEEDINGS{Kogler:642399,
      author       = {Kogler, Roman and Murnauer, Josef Modestus and Kluth,
                      Stefan and Britzger, Daniel},
      title        = {{M}achine {L}earning {A}ssisted {R}econstruction of
                      {H}adron-{C}ollider {E}vents using {M}ini-{J}ets},
      reportid     = {PUBDB-2025-05550},
      year         = {2025},
      abstract     = {Reconstructing impactful physical observables from hadron
                      collider data represents challenges due to combinatorial
                      ambiguities and experimental effects. We propose a novel
                      approach using mini-jets (R=0.1) as the sole reconstructed
                      objects, employing a deep neural network for observable
                      determination. This method condenses full event information
                      into a manageable size, demonstrating superior efficiency
                      and generality compared to classical algorithms for future
                      LHC analyses.},
      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-other-20150101},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://bib-pubdb1.desy.de/record/642399},
}