6.7960 | Fall 2024 | Undergraduate, Graduate

Deep Learning

Lec 05. Architectures: Graphs

This lecture covers graph neural networks (GNNs), showing connections to MLPs and CNNs and message-passing algorithms. We will also discuss theoretical limitations on the expressive power of GNNs, and the practical implications of this.

Learning Resource Types
Lecture Notes
Lecture Videos
Problem Sets
Projects with Examples
Readings