Uploaded February 2021 | Updated September 2026, 2 weeks ago
MIT 6.S191 (2021): Introduction to Deep Learning
Deep Generative Modeling
Lecturer: Ava Soleimany
January 2021
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 - Introduction
6:03 - Why care about generative models?
8:56 - Latent variable models
11:31 - Autoencoders
17:00 - Variational autoencoders
24:30 - Priors on the latent distribution
34:38 - Reparameterization trick
38:14 - Latent perturbation and disentanglement
41:25 - Debiasing with VAEs
43:42 - Generative adversarial networks
46:14 - Intuitions behind GANs
48:27 - Training GANs
52:57 - GANs: Recent advances
57:15 - CycleGAN of unpaired translation
1:01:01 - Summary
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MIT 6.S191 (2021): Introduction to Deep Learning
Deep Generative Modeling
Lecturer: Ava Soleimany
January 2021
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 - Introduction
6:03 - Why care about generative models?
8:56 - Latent variable models
11:31 - Autoencoders
17:00 - Variational autoencoders
24:30 - Priors on the latent distribution
34:38 - Reparameterization trick
38:14 - Latent perturbation and disentanglement
41:25 - Debiasing with VAEs
43:42 - Generative adversarial networks
46:14 - Intuitions behind GANs
48:27 - Training GANs
52:57 - GANs: Recent advances
57:15 - CycleGAN of unpaired translation
1:01:01 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!
