An Introduction to Variational Autoencoders

Download or Read eBook An Introduction to Variational Autoencoders PDF written by Diederik P. Kingma and published by . This book was released on 2019-11-12 with total page 102 pages. Available in PDF, EPUB and Kindle.
An Introduction to Variational Autoencoders
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Total Pages : 102
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ISBN-10 : 1680836226
ISBN-13 : 9781680836226
Rating : 4/5 (26 Downloads)
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Book Synopsis An Introduction to Variational Autoencoders by : Diederik P. Kingma

Book excerpt: An Introduction to Variational Autoencoders provides a quick summary for the of a topic that has become an important tool in modern-day deep learning techniques.


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Dynamical Variational Autoencoders: Introduction 2. Variational Autoencoders 3. Recurrent Neural Networks and State Space Models 4. Definition of Dynamical VAEs 5. Deep Kalman Filters 6. Kalman Variational Autoencoders 7. STOchastic Recurrent Networks 8. Variational Recurrent Neural Networks 9. Stochastic Recurrent Neural Networks 10. Recurrent Variational Autoencoders 11. Disentangled Sequential Autoencoders 12. Brief tour of other models 13. Experiments 14. Discussion Acknowledgements Appendices References
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Generative Deep Learning
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