ResNet models classify four particle types and regress vertex, direction, and momentum in Hyper-Kamiokande with resolutions matching likelihood methods but at 30,000-50,000x faster inference on GPU.
Jiang, et al., Atmospheric Neutrino Oscillation Analysis with Improved Event Reconstruction in Super-Kamiokande IV, PTEP 2019 (5) (2019) 053F01
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
hep-ex 1years
2026 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Enhancing Event Reconstruction in Hyper-Kamiokande with Machine Learning: A ResNet Implementation
ResNet models classify four particle types and regress vertex, direction, and momentum in Hyper-Kamiokande with resolutions matching likelihood methods but at 30,000-50,000x faster inference on GPU.