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Advanced Deep Learning with Keras

You're reading from Advanced Deep Learning with Keras

Product type Book

Published in Oct 2018

Publisher Packt

ISBN-13 9781788629416

Pages 368 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Rowel Atienza

Table of Contents (13) Chapters

Preface

1. Introducing Advanced Deep Learning with Keras

2. Deep Neural Networks

3. Autoencoders

4. Generative Adversarial Networks (GANs)

5. Improved GANs

6. Disentangled Representation GANs

7. Cross-Domain GANs

8. Variational Autoencoders (VAEs)

9. Deep Reinforcement Learning

10. Policy Gradient Methods

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Index

References

Sutton and Barto. Reinforcement Learning: An Introduction, 2017 (http://incompleteideas.net/book/bookdraft2017nov5.pdf).
Volodymyr Mnih and others, Human-level control through deep reinforcement learning. Nature 518.7540, 2015: 529 (http://www.davidqiu.com:8888/research/nature14236.pdf)
Hado Van Hasselt, Arthur Guez, and David Silver Deep Reinforcement Learning with Double Q-Learning. AAAI. Vol. 16, 2016 (http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/download/12389/11847).
Kai Arulkumaran and others A Brief Survey of Deep Reinforcement Learning. arXiv preprint arXiv:1708.05866, 2017 (https://arxiv.org/pdf/1708.05866.pdf).
David Silver Lecture Notes on Reinforcement Learning, (http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html).
Tom Schaul and others. Prioritized experience replay. arXiv preprint arXiv:1511.05952, 2015 (https://arxiv.org/pdf/1511.05952.pdf).
Ziyu Wang and others. Dueling Network Architectures for Deep Reinforcement Learning. arXiv preprint arXiv:1511...

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Authors (1)

Rowel Atienza

Rowel Atienza is an Associate Professor at the Electrical and Electronics Engineering Institute of the University of the Philippines, Diliman. He holds the Dado and Maria Banatao Institute Professorial Chair in Artificial Intelligence. Rowel has been fascinated with intelligent robots since he graduated from the University of the Philippines. He received his MEng from the National University of Singapore for his work on an AI-enhanced four-legged robot. He finished his Ph.D. at The Australian National University for his contribution on the field of active gaze tracking for human-robot interaction. Rowel's current research work focuses on AI and computer vision. He dreams on building useful machines that can perceive, understand, and reason. To help make his dreams become real, Rowel has been supported by grants from the Department of Science and Technology (DOST), Samsung Research Philippines, and Commission on Higher Education-Philippine California Advanced Research Institutes (CHED-PCARI).

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