key words
Generative adversarial networks
abstract
provide a review on various GANs methods from theperspectives of algorithms, theory, and applications
- the motivations, mathematical representations, and structure of most GANsalgorithms
- compares the commonalitiesand differences of these GANs methods(semi-supervised learning, transfer learning, and reinforcement learning)
- theoretical issues
- typical applications
- future problems