Mastering Machine Learning Algorithms - Second Edition

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Introduction to Generative Adversarial Networks

In this chapter, we're going to provide a brief introduction to a family of generative models based on some game theory concepts. Their main peculiarity is an adversarial training procedure that is aimed at learning to distinguish between true and fake samples, driving, at the same time, another component that generates samples more and more similar to the training examples.

In particular, we will be discussing:

• Adversarial training and standard Generative Adversarial Networks (GANs)
• Deep Convolutional GANs (DCGANs)
• Wasserstein GANs (WGANs)

We can now introduce the concept of adversarial training of neural models, its connection to game theory and its applications to GANs.

Adversarial training ...