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An Introduction to Variational Autoencoders - Research Book

An Introduction to Variational Autoencoders - Research Book

Great Research Book in An Introduction to Variational Autoencoders

Author(s) Name:  Diederik P. Kingma; Max Welling

About the Book:

   In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models and corresponding inference models using stochastic gradient descent. The framework has a wide array of applications from generative modeling, semi-supervised learning to representation learning.
   The authors expand earlier work and provide the reader with the fine detail on the important topics giving deep insight into the subject for the expert and student alike. Written in a survey-like nature the text serves as a review for those wishing to quickly deepen their knowledge of the topic.
   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.

Table of contents:

1. Introduction
2. Variational Autoencoders
3. Beyond Gaussian Posteriors
4. Deeper Generative Models
5. Conclusion

ISBN:  9781680836226

Publisher:  Now Foundations and Trends

Year of Publication:  2019

Book Link:  Home Page Url