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: 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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[@ML-DS-AI-Projects]

First thank you Alexander and Ava for sharing the knowledge After watching these videos, I realized that learning machine learning is not just a skill; teaching is a much bigger skill.

[@freddybrou405]

Thank you so much for the course. So much interesting.

[@erikkim4739]

so excited for this!

[@pradyumnanimbkar8011]

Cool and well-sorted.

[@civilengineeringonlinecour7143]

Awesome lecture. 🎉

[@catalinmanea1560]

awesome, many thanks for your initiative ! keep up the great work

[@4threich166]

Beauty with brain ❤

[@arpandas2758]

thank you for the amazing content, please add the slides for this lecture in the website, its still not there, cheers :)

[@4threich166]

Queen

[@shakshamkarki7061]

Not a MITian but learning in MIT

[@ahmedelsafty6654]

First thank you Ava for sharing the knowledge. I'm not able to understand, why the standard auto-encoder does a deterministic operation?

[@genkideska4486]

5 mins more let's gooooo

[@Lima3578user]

Spellbound by the lecture, great insights. Is she Indian

[@dragonartgroup6982]

She's Persian

[@geoffreyporto]

I have a dataset of 120 images of cell phone photographs of the skin of dogs sick with 12 types of skin diseases, with a distribution of 10 images for each dog. What type of Generative Adversarial Network (GAN) is most suitable to increase my dataset with quality and be able to train my DL model? DcGAN, ACGAN, StyleGAN3, CGAN?

[@TechWithAbee]

just try them out

[@faridsaud6567]

Try fine tuning the models with your data

[@aurabless7552]

when gpt 4o lectures :D

[@gapcreator726]

Nice amini teaching❤ and your curly hair nice😮