Lecture part A
Lecture part B
In this section, we covered the implementation of Generative models viz. Undercomplete Autoencoder, Denoising Autoencoders, Variational Autoencoders and Generative Adversarial Networks. We analyze these models from the perpesective of the framework of Energy Based Models (EBM). In doing so, we realize that these generative models can be considered as extenstions of EBMs and differ from each other with subtle architectural adjustments.