Code for the paper "Bayesian Differential Privacy for Machine Learning" (https://arxiv.org/pdf/1901.09697.pdf).
The main code for Bayesian accounant is located in bayesian_privacy_accounant.py.
File scaled_renyi.py contains a function to compute scaled Renyi divergence of two Gaussian distributions with equal variances. In a similar fashion, functions for other distributions can be added to accomodate other privacy mechanisms.
IPython notebooks implement experiments from the paper.
Please cite our paper if find the code helpful:
@inproceedings{triastcyn2020bayesian,
author = {Triastcyn, Aleksei and Faltings, Boi},
title = {Bayesian Differential Privacy for Machine Learning},
booktitle = {International Conference on Machine Learning},
year = {2020}
}