NIPS 2016 Tutorial: Generative Adversarial Networks
It provides an educational overview of GANs for researchers and practitioners, but is incremental as it synthesizes existing knowledge without new results.
This tutorial summarizes the presentation on generative adversarial networks (GANs) at NIPS 2016, covering their principles, comparisons to other models, and state-of-the-art applications in image generation.
This report summarizes the tutorial presented by the author at NIPS 2016 on generative adversarial networks (GANs). The tutorial describes: (1) Why generative modeling is a topic worth studying, (2) how generative models work, and how GANs compare to other generative models, (3) the details of how GANs work, (4) research frontiers in GANs, and (5) state-of-the-art image models that combine GANs with other methods. Finally, the tutorial contains three exercises for readers to complete, and the solutions to these exercises.