Neural posterior estimation reconstructs neutrino energy, direction, and flavor from radio signals in ice detectors, reporting median resolutions of 0.30 log(E) and 18 sq deg (shallow) and 0.08 log(E) and 28 sq deg (deep) for NC events at 1 EeV.
Gl¨ usenkamp,Unifying supervised learning and VAEs: coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions,Eur
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Event Reconstruction for Radio-Based In-Ice Neutrino Detectors with Neural Posterior Estimation
Neural posterior estimation reconstructs neutrino energy, direction, and flavor from radio signals in ice detectors, reporting median resolutions of 0.30 log(E) and 18 sq deg (shallow) and 0.08 log(E) and 28 sq deg (deep) for NC events at 1 EeV.