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GNN-Based Muon Energy Reconstruction for INO-ICAL

This project employs a Graph Neural Network (GNN) to reconstruct the energy of muons in the proposed India-based Neutrino Observatory (INO-ICAL) experiment. More detailed information can be found in the following link.

The graph dataset used for this project has already been prepared and is available in this repository.

The dataset was simulated using ICAL, and the source code for the simulation is accessible here.

The notebook contains the code for performing energy classification using a Graph Neural Network (GNN).