Computational appendix of "Physics solutions to machine learning privacy leaks" [arXiv:2202.12319]

This repository contains the codes used for the article "Physics solutions to machine learning privacy leaks. Alejandro Pozas-Kerstjens, Senaida Hernández-Santana, José Ramón Pareja Monturiol, Marco Castrillón López, Giannicola Scarpa, Carlos E. González-Guillén, and David Pérez-García. arXiv:2202.12319." It provides the codes for cleaning the global.health database, training neural network and matrix product state models on the dataset generated, and attacking the models via shadow training.

All code is written in Python.