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Found 3 papers, 2 papers with code
GraphNeT: Graph neural networks for neutrino telescope event reconstruction
GraphNeT is an open-source python framework aimed at providing high quality, user friendly, end-to-end functionality to perform reconstruction tasks at neutrino telescopes using graph neural networks (GNNs).
Learning optimal wavelet bases using a neural network approach
A novel method for learning optimal, orthonormal wavelet bases for representing 1- and 2D signals, based on parallels between the wavelet transform and fully connected artificial neural networks, is described.
Decorrelated Jet Substructure Tagging using Adversarial Neural Networks
We describe a strategy for constructing a neural network jet substructure tagger which powerfully discriminates boosted decay signals while remaining largely uncorrelated with the jet mass.
