Graph Autoencoder (GAE) and Variational Graph Autoencoder (VGAE)
In this tutorial, we present the theory behind Autoencoders, then we show how Autoencoders are extended to Graph Autoencoder (GAE) by Thomas N. Kipf.
Then, we explain a simple implementation taken from the official PyTorch Geometric GitHub repository[here].
In the second part of the Tutorial, the theory of Variational Autoencoders and Variational Graph Autoencoders is explained.
Finally, we compare the results obtained by the previous Networks (GAE) and (VGAE) using Tensorboard.
Download the material of the lecture here.