This is the implementaiton of "Differentially Private Releasing via Deep Generative Models", which trains GAN models in a differentially private manner such that the models can be used to synthesize data for downstream tasks.
If you used the source code, please cite: Xinyang Zhang, Shouling Ji, and Ting Wang, Differentially Private Releasing via Deep Generative Model, arXiv e-prints, 2018.
The current implementation supports the datasets including MNIST, CelebA, and LSUN.
Check the folder dpgan/src/dp.