MIT Introduction to Deep Learning 6.S191: Lecture 4
Deep Generative Modeling
Lecturer: Ava Amini
New 2024 Edition

For all lectures, slides, and lab materials: http://introtodeeplearning.com​

Lecture Outline
0:00​ Introduction
6:10 Why care about generative models?
8:16​ Latent variable models
10:50​ Autoencoders
17:02​ Variational autoencoders
23:25 Priors on the latent distribution
32:31​ Reparameterization trick
34:36​ Latent perturbation and disentanglement
37:40 Debiasing with VAEs
39:37​ Generative adversarial networks
42:09​ Intuitions behind GANs
44:57 Training GANs
48:28 GANs: Recent advances
50:57 CycleGAN of unpaired translation
55:03 Diffusion Model sneak peak

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