1. Introduction

3. Mode Collapse Problem in GAN

4. Maximum Likelihood Estimation in GAN

5. Other Variants of GAN

6. Sampling and Interpolation in GAN

7. Applications of GAN

8. Autoencoders Based on Adversarial Learning

9. Conclusion