Must-Read Papers on GANs – Towards Data Science

I would recommend starting your GAN journey with the DCGAN paper. This paper shows how convolutional layers can be used with GANs and provides a series of additional architectural guidelines for doing this. The paper also discusses topics such as Visualizing GAN features, Latent space interpolation, using discriminator features to train classifiers, and evaluating results. All of these additional topics are bound to come up in your GAN research. In summation, the DCGAN paper is a must-read GAN paper because it defines the architecture in such a clear way that it is easy to get started with some code and begin developing an intuition for GANs.