How Generative Adversarial Networks and Its Variants Work : An Overview of GAN

By Yongjun Hong, Uiwon Hwang, Jaeyoon Yoo, Sungroh Yoon. 2017

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Garrett Wilson
2. Diane Joyce Cook
3. Michihiro Kuramochi
4. Charu C. Aggarwal
5. Narayanan Chatapuram Krishnan
6. Mukund Deshpande
7. George Karypis
8. Manuel Jesus Cobo

Citations in the corpus

• Adversarial Transfer Learning (2018, background): “For a more in-depth discussion of these methods, there are a number of survey papers directed at GAN variants that include a discussion of training challenges and work [52, 54, 79].”