WavePID improves cascade purity and classification performance in low-energy IceCube events by adding single-PMT timing observables to a graph neural network morphology classifier.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
New graph neural network and convolutional neural network reconstructions of neutrino inelasticity are developed and used to statistically separate neutrinos from antineutrinos, yielding updated neutrino mass ordering sensitivities for IceCube DeepCore and Upgrade.
In the minimal pseudo-Dirac HNL scenario, light-neutrino oscillation data fixes an ellipse in the active flavour simplex for leading active-heavy interactions via a single complex amplitude and Majorana phase.
citing papers explorer
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WavePID: Low-energy flavor identification using single-PMT time series in IceCube
WavePID improves cascade purity and classification performance in low-energy IceCube events by adding single-PMT timing observables to a graph neural network morphology classifier.
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Incorporating Inelasticity Reconstruction into Neutrino Mass Ordering Studies with IceCube
New graph neural network and convolutional neural network reconstructions of neutrino inelasticity are developed and used to statistically separate neutrinos from antineutrinos, yielding updated neutrino mass ordering sensitivities for IceCube DeepCore and Upgrade.
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Neutrino oscillation data and a pseudo-Dirac heavy neutral lepton
In the minimal pseudo-Dirac HNL scenario, light-neutrino oscillation data fixes an ellipse in the active flavour simplex for leading active-heavy interactions via a single complex amplitude and Majorana phase.