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Variational Methods for Machine Learning with Applications to Deep Networks

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Variational Methods for Machine Learning with Applications to Deep Networks
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Fundamentals of Statistical Inference
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    Chapter 3 Model-Based Machine Learning and Approximate Inference
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    Chapter 4 Bayesian Neural Networks
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    Chapter 5 Variational Autoencoder
Attention for Chapter 3: Model-Based Machine Learning and Approximate Inference
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