graphnet-team/graphnet
A Deep learning library for neutrino telescopes
This tool helps high-energy physicists and astrophysicists analyze data from neutrino telescopes like IceCube or KM3NeT. It takes raw event data from these detectors and processes it to reconstruct neutrino interactions, providing highly accurate information about the energy, direction, and type of neutrinos. Researchers use this to perform tasks such as searching for cosmic neutrino sources or studying neutrino oscillations.
111 stars.
Use this if you are a physicist working with neutrino telescope data and need to perform fast, state-of-the-art event reconstruction and classification using deep learning techniques.
Not ideal if your research does not involve neutrino telescopes or requires classical data analysis methods rather than deep learning.
Stars
111
Forks
112
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 24, 2026
Commits (30d)
0
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