An Introduction to Variational Autoencoders

An Introduction to Variational Autoencoders
Author: DIEDERIK P. KINGMA;MAX WELLING.
Publisher:
Total Pages: 94
Release: 2019
Genre:
ISBN: 9781680836233

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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.


An Introduction to Variational Autoencoders
Language: en
Pages: 94
Authors: DIEDERIK P. KINGMA;MAX WELLING.
Categories:
Type: BOOK - Published: 2019 - Publisher:

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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
An Introduction to Variational Autoencoders
Language: en
Pages: 102
Authors: Diederik P. Kingma
Categories: Computers
Type: BOOK - Published: 2019-11-12 - Publisher:

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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
Deep Learning
Language: en
Pages: 801
Authors: Ian Goodfellow
Categories: Computers
Type: BOOK - Published: 2016-11-10 - Publisher: MIT Press

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An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and res
Variational Methods for Machine Learning with Applications to Deep Networks
Language: en
Pages: 173
Authors: Lucas Pinheiro Cinelli
Categories: Technology & Engineering
Type: BOOK - Published: 2021-05-10 - Publisher: Springer Nature

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This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models. Starting from the mod
Generative Deep Learning
Language: en
Pages: 360
Authors: David Foster
Categories: Computers
Type: BOOK - Published: 2019-06-28 - Publisher: "O'Reilly Media, Inc."

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Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and compos