# MIT 6.S191: Deep Generative Modeling

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

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!!

sortSort By