1 citations · 1 across the 6 of their papers we have counts for
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Self-Supervised Learning Strategies for Jet Physics
Patrick Rieck, Kyle Cranmer, Etienne Dreyer +5
We extend the re-simulation-based self-supervised learning approach to learning representations of hadronic jets in colliders by exploiting the Markov property of the standard simu…
Point Cloud Deep Learning Methods for Particle Shower Reconstruction in the DHCAL
Maryna Borysova, Shikma Bressler, Eilam Gross +2
Precision measurement of hadronic final states presents complex experimental challenges. The study explores the concept of a gaseous Digital Hadronic Calorimeter (DHCAL) and discus…
PASCL: Supervised Contrastive Learning with Perturbative Augmentation for Particle Decay Reconstruction
Junjian Lu, Siwei Liu, Dmitrii Kobylianski +3
In high-energy physics, particles produced in collision events decay in a format of a hierarchical tree structure, where only the final decay products can be observed using detecto…