2023
PAC-Bayesian Generalization Bounds for Adversarial Generative Models
ICML 2023poster
We extend PAC-Bayesian theory to generative models and develop generalization bounds for models based on the Wasserstein distance and the total variation distance. Our first result on the Wasserstein distance assumes the instance space is bounded, while our second result takes advantage of dimension…