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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