An Introduction to Variational Autoencoders

Diederik P. Kingma, Max Welling (Autoren)

Buch | Softcover

102 Seiten

2019
now publishers Inc (Verlag)
9781680836226 (ISBN)

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Presents 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.

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.

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

Erscheinungsdatum	02.12.2019
Reihe/Serie	Foundations and Trends® in Machine Learning
Verlagsort	Hanover
Sprache	englisch
Maße	156 x 234 mm
Gewicht	156 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
ISBN-13	9781680836226 / 9781680836226
Zustand	Neuware