Training generative neural networks via Maximum Mean Discrepancy optimization

Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani

We consider training a deep neural network to generate samples from an unknown distribution given i.i.d. data. We frame learning as an optimization minimizing a two-sample test sta…