You're reading from Hands-On Generative Adversarial Networks with Keras

Product typeBook

Published inMay 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789538205

Edition1st Edition

Languages

Python

Tools

Keras

Concepts

Neural Networks

Author (1)

Rafael Valle

Summary

In this chapter, we explored the use of GANs in the context of discrete time-series prediction. We learned how to implement a model for a generator of discrete sequences with a short vocabulary based on the Adversarial Generation of Natural Language paper by Rajeswar et al. We implemented the models and trained them on sequences of words and sequences of characters.

In the next chapter, we will learn how to perform text-to-image synthesis with GANs.

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Hands-On Generative Adversarial Networks with Keras

Published in: May 2019Publisher: PacktISBN-13: 9781789538205

Author (1)

Rafael Valle

Rafael Valle is a research scientist at NVIDIA focusing on audio applications. He has years of experience developing high performance machine learning models for data/audio analysis, synthesis and machine improvisation with formal specifications. Dr. Valle was the first to generate speech samples from scratch with GANs and to show that simple yet efficient techniques can be used to identify GAN samples. He holds an Interdisciplinary PhD in Machine Listening and Improvisation from UC Berkeley, a Masters degree in Computer Music from the MH-Stuttgart in Germany and a Bachelors degree in Orchestral Conducting from UFRJ in Brazil.
Read more about Rafael Valle

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Author (1)

Hands-On Generative Adversarial Networks with PyTorch 1.x

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