The paper, Trigger-Level Event Reconstruction for Neutrino Telescopes Using Sparse Submanifold Convolutional Neural Networks, is here https://arxiv.org/abs/2303.08812.
The crucial advantage of SSCNN are that they "replaces traditional convolutions with sparse submanifold convolutions" which operate "only on the non-zero elements" and creates efficiencies.
The crucial advantage of SSCNN are that they "replaces traditional convolutions with sparse submanifold convolutions" which operate "only on the non-zero elements" and creates efficiencies.