MIT Introduction to Deep Learning 6.S191: Lecture 4
Deep Generative Modeling
Lecturer: Ava Amini
2023 Edition
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 - Introduction
5:48 - Why care about generative models?
7:33 - Latent variable models
9:30 - Autoencoders
15:03 - Variational autoencoders
21:45 - Priors on the latent distribution
28:16 - Reparameterization trick
31:05 - Latent perturbation and disentanglement
36:37 - Debiasing with VAEs
38:55 - Generative adversarial networks
41:25 - Intuitions behind GANs
44:25 - Training GANs
50:07 - GANs: Recent advances
50:55 - Conditioning GANs on a specific label
53:02 - CycleGAN of unpaired translation
56:39 - Summary of VAEs and GANs
57:17 - Diffusion Model sneak peak
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