Further reading

• Generative Adversarial Networks, Ian J Goodfellow and others (2014): https://arxiv.org/abs/1406.2661
• On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes, Andrew Y Ng and Michael I. Jordan (2002): https://ai.stanford.edu/~ang/papers/nips01-discriminativegenerative.pdf
• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, Radford et al (2016): https://arxiv.org/pdf/1511.06434.pdf
• Conditional Generative Adversarial Nets, Mehdi Mirza and Simon Osindero (2014): https://arxiv.org/pdf/1411.1784.pdf
• Unrolled Generative Adversarial Networks, Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein (2016): https://arxiv.org/abs/1611.02163
• Wasserstein GAN, Martin Arjovsky, Soumith Chintala, Léon Bottou (2017): https://arxiv.org/pdf/1701.07875.pdf.
• Improved Training of Wasserstein GANs...