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An Introduction to Modern
Statistical Learning
Preface
1
Introduction
I
Representation and Inference
II
Learning
6
A Mathematical Framework for Learning
7
Learning Discriminative Models
8
Learning Generative Models with Latent Variables
9
Learning Invertible Generative Models
10
Learning Non-Invertible Generative Models
10.1
Sparse coding with Gaussian recognition models
10.2
Variational Autoencoders
10.3
Diffusion Models
10.4
Variational inference
11
Learning with Reparameterizations
12
Learning Energy-Based Models
III
Appendices
10.4
Variational inference