Comprehensive reconstruction of collider events with hypergraph representation learning and graph-conditioned diffusion

Paper recorded by Signals 4 on 2026-09-16 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17

Category: cs.LG · 机器学习 · first seen 2026-09-17

Abstract

In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter from the stable final states recorded by detectors. We decompose event reconstruction into two primary tasks: assigning measured jets and charged leptons to parent particles, and predicting unmeasured neutrino kinematics. We present VyPER, a novel geo

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