Spectral-based Graph Convolutional Network for Directed Graphs

Understand

Graph convolutional networks(GCNs) have become the most popular approaches for graph data in these days because of their powerful ability to extract features from graph.

• GCNs approaches are divided into two categories, spectral-based and spatial-based.
• As the earliest convolutional networks for graph data, spectral-based GCNs have achieved impressive results in many graph related analytics tasks.
• However, spectral-based models cannot directly work on directed graphs.