Differentially Private Gradient Flow based on the Sliced Wasserstein Distance

Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi +4

Safeguarding privacy in sensitive training data is paramount, particularly in the context of generative modeling. This can be achieved through either differentially private stochas…