Graph Neural Networks: Architectures, Stability and Transferability

Understand

Graph Neural Networks (GNNs) are information processing architectures for signals supported on graphs.

• They are presented here as generalizations of convolutional neural networks (CNNs) in which individual layers contain banks of graph convolutional filters instead of banks of classical convolutional filters.
• Otherwise, GNNs operate as CNNs.
• Filters are composed with pointwise nonlinearities and stacked in layers.