How Curvature Enhance the Adaptation Power of Framelet GCNs

Understand

Graph neural network (GNN) has been demonstrated powerful in modeling graph-structured data.

• However, despite many successful cases of applying GNNs to various graph classification and prediction tasks, whether the graph geometrical information has been fully exploited to enhance the learning performance of GNNs is not yet well understood.
• This paper introduces a new approach to enhance GNN by discrete graph Ricci curvature.
• Specifically, the graph Ricci curvature defined on the edges of a graph measures how difficult the information transits on one edge from one node to another based on their neighborhoods.