MIT 6.S191 (2021): Deep Generative Modeling
Alexander Amini Alexander Amini
239K subscribers
105,722 views
0

 Published On Premiered Feb 26, 2021

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!!

show more

Share/Embed