Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily

Graph Convolutional Networks (GCNs) have been widely applied in various fields due to their significant power on processing graph-structured data. Typical GCN and its variants work under a homophily assumption (i.e., nodes with same class are prone to connect to each other), while ignoring the heter... View More