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Deep Learning Quick Reference
book

Deep Learning Quick Reference

by Mike Bernico
March 2018
Intermediate to advanced
272 pages
7h 53m
English
Packt Publishing
Content preview from Deep Learning Quick Reference

Deep Convolutional GAN architecture

There are many papers on GANs, each proposing new novel architectures and tweaks; however, most of them are at least somewhat based on the Deep Convolutional GAN (DCGAN). For the rest of the chapter, we will be focusing on this model because this knowledge will hopefully serve you well as you take on new and exciting GAN architectures that aren't covered here, such as the Conditional GAN (cGAN), the Stack GAN, the InfoGAN, or the Wasserstein GAN, or possibly some other new variant that you might choose to look at next.

The DCGAN was introduced by Alex Radford, Luke Metz, and Soumith Chintala in the paper Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (https://arxiv.org/pdf/1511.06434.pdf ...

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Publisher Resources

ISBN: 9781788837996Supplemental Content