A transformer-encoded spherical normalizing flow achieves state-of-the-art angular resolution for IceCube neutrino tracks and showers, improving median resolution by factors of 1.3-2.5 over B-spline likelihoods at 100 TeV and outperforming prior ML methods for muons.
A convolutional neural network based cascade reconstruction for the IceCube Neutrino Observatory.Journal of Instrumentation, 16(07):P07041, 2021
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Neural posterior estimation of the neutrino direction in IceCube using transformer-encoded normalizing flows on the sphere
A transformer-encoded spherical normalizing flow achieves state-of-the-art angular resolution for IceCube neutrino tracks and showers, improving median resolution by factors of 1.3-2.5 over B-spline likelihoods at 100 TeV and outperforming prior ML methods for muons.