Hands-On Transfer Learning with Python

Generative Adversarial Networks

Generative Adversarial Networks (GANs) have gained a lot of popularity since their first introduction in a 2014 NIPS paper by Ian Goodfellow and their co-authors (https://arxiv.org/pdf/1406.2661.pdf). Now we see applications of GANs in various domains. Researchers from Insilico Medicine proposed an approach to artificial drug discovery using GANs. They also found applications in image processing and video processing problems, such as image style transfers and deep convolutional generative adversarial networks (DCGAN).

As the name suggests, this is another type of generative model that uses neural networks. GANs have two main components—a generator neural network and a discriminator neural network. The generator ...