A Deep learning library for neutrino telescopes
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Updated
Oct 21, 2025 - Python
A Deep learning library for neutrino telescopes
Tree-level completions of LNV operators for neutrino-mass model building
Scalable Particle Imaging with Neural Embeddings
Application of ML for Neutrino Physics experiment LEGEND-200
An open source machine learning framework that provides predictions for all-energy neutrino structure functions.
Tensor based engine for calculating neutrino oscillation probabilities in a fast, flexible, and differentiable way
Reconstruction library for a 3D LiquidO detector
Convolutional networks (and CapsNET) for SuperNEMO tracker
Monte Carlo based generator of neutrino induced dimuon events. Simulates muons from heavy quark (charm) production and Trident production. Container with all software dependencies provided for future developments.
Geometric Information Field Theory: E₈×E₈ topological unification of particle physics. 0.13% precision across 34 observables with 3 parameters.
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