Course website: http://bit.ly/DLSP20-web
Playlist: http://bit.ly/pDL-YouTube
Speaker: Alfredo Canziani
Week 8: http://bit.ly/DLSP20-08
0:00:00 – Week 8 – Practicum
PRACTICUM: http://bit.ly/DLSP20-08-3
In this section, we discussed a specific type of generative model called Variational Autoencoders and compared their functionalities and advantages over Classic Autoencoders. We explored the objective function of VAE in detail, understanding how it enforced some structure in the latent space. Finally, we implemented and trained a VAE on the MNIST dataset and used it to generate new samples.
0:02:35 – Autoencoders (AEs) vs. variational autoencoders (VAEs)
0:16:37 – Understanding the VAE objective function
0:31:33 – Notebook example for variational autoencoder
