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Topological Reconstruction of Particle Physics Processes using Graph
Neural Networks

v1v2v3v4v5 (latest)

Topological Reconstruction of Particle Physics Processes using Graph Neural Networks

24 March 2023

ArXiv (abs)PDF HTML

Papers citing "Topological Reconstruction of Particle Physics Processes using Graph Neural Networks"

3 / 3 papers shown

PASCL: Supervised Contrastive Learning with Perturbative Augmentation
for Particle Decay Reconstruction

PASCL: Supervised Contrastive Learning with Perturbative Augmentation for Particle Decay Reconstruction

Dmitrii Kobylianski

179

3

0

18 Feb 2024

Reconstruction of Unstable Heavy Particles Using Deep
Symmetry-Preserving Attention Networks

Reconstruction of Unstable Heavy Particles Using Deep Symmetry-Preserving Attention NetworksCommunications Physics (CP), 2023

Alexander Shmakov

218

11

0

05 Sep 2023

$ν^2$-Flows: Fast and improved neutrino reconstruction in
multi-neutrino final states with conditional normalizing flows

ν^2

-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows

257

21

0

05 Jul 2023