Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions

Zeyuan Allen-Zhu, Yuanzhi Li

Generative adversarial networks (GANs) are among the most successful models for learning high-complexity, real-world distributions. However, in theory, due to the highly non-convex…