TY  - CONF
AU  - Kogler, Roman
AU  - Murnauer, Josef  Modestus
AU  - Kluth, Stefan
AU  - Britzger, Daniel
TI  - Machine Learning Assisted Reconstruction of Hadron-Collider Events using Mini-Jets 
M1  - PUBDB-2025-05550
PY  - 2025
AB  - 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.
T2  - DPG Spring Meeting (German Physical Society)
CY  - 31 Mar 2025 - 4 Apr 2025, Göttingen (Germany)
Y2  - 31 Mar 2025 - 4 Apr 2025
M2  - Göttingen, Germany
LB  - PUB:(DE-HGF)6
UR  - https://bib-pubdb1.desy.de/record/642399
ER  -