2019
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization
ICML 2019oral
This paper provides a simple procedure to fit generative networks to target distributions, with the goal of a small Wasserstein distance (or other optimal transport costs). The approach is based on two principles: (a) if the source randomness of the network is a continuous distribution (the "semi-di…