%0 Conference Paper
%A Kogler, Roman
%A Murnauer, Josef Modestus
%A Kluth, Stefan
%A Britzger, Daniel
%T Machine Learning Assisted Reconstruction of Hadron-Collider Events using Mini-Jets
%M PUBDB-2025-05550
%D 2025
%X 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.
%B DPG Spring Meeting (German Physical Society)
%C 31 Mar 2025 - 4 Apr 2025, Göttingen (Germany)
Y2 31 Mar 2025 - 4 Apr 2025
M2 Göttingen, Germany
%F PUB:(DE-HGF)6
%9 Conference Presentation
%U https://bib-pubdb1.desy.de/record/642399