Foundations

Understand autoencoders through encoding, latent representations, and reconstruction, then see how graph autoencoders use GNNs to learn node attributes and graph structure.

An introduction to graph neural networks through graph structure, neighborhood aggregation, message passing, and the shared logic behind GCN, GraphSAGE, and GAT.