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Advanced Deep Learning with Keras

You're reading from   Advanced Deep Learning with Keras Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788629416
Length 368 pages
Edition 1st Edition
Languages
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Author (1):
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Rowel Atienza Rowel Atienza
Author Profile Icon Rowel Atienza
Rowel Atienza
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Table of Contents (13) Chapters Close

Preface 1. Introducing Advanced Deep Learning with Keras FREE CHAPTER 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 Other Books You May Enjoy Index

References

  1. Diederik P. Kingma and Max Welling. Auto-encoding Variational Bayes. arXiv preprint arXiv:1312.6114, 2013(https://arxiv.org/pdf/1312.6114.pdf).
  2. Kihyuk Sohn, Honglak Lee, and Xinchen Yan. Learning Structured Output Representation Using Deep Conditional Generative Models. Advances in Neural Information Processing Systems, 2015(http://papers.nips.cc/paper/5775-learning-structured-output-representation-using-deep-conditional-generative-models.pdf).
  3. Yoshua Bengio, Aaron Courville, and Pascal Vincent. Representation Learning: A Review and New Perspectives. IEEE transactions on Pattern Analysis and Machine Intelligence 35.8, 2013: 1798-1828(https://arxiv.org/pdf/1206.5538.pdf).
  4. Xi Chen and others. Infogan: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets. Advances in Neural Information Processing Systems, 2016(http://papers.nips.cc/paper/6399-infogan-interpretable-representation-learning-by-information-maximizing-generative-adversarial-nets.pdf...
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