Adaptive Graph Convolutional Neural Networks

Understand

Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks.

• Current filters in graph CNNs are built for fixed and shared graph structure.
• However, for most real data, the graph structures varies in both size and connectivity.
• The paper proposes a generalized and flexible graph CNN taking data of arbitrary graph structure as input.