We implemented a ResNet architecture to perform a regression task on High Energy Physics data from the Jiangmen Underground Neutrino Observatory experiment and we developed a Quantum ML model (Trainable Quanvolutional Neural Network) to perform the same task on the simplified data.
GiacomoFrn/qcnn4juno
Classical and Quantum Machine Learning tools for an High Energy Physics task - Final project for Laboratory of Computational Physics module B
Jupyter Notebook