Graph Cross Networks with Vertex Infomax Pooling
Graph Cross Networks with Vertex Infomax Pooling
We propose a novel graph cross network (GXN) to achieve comprehensive feature learning from multiple scales of a graph. Based on trainable hierarchical representations of a graph, GXN enables the interchange of intermediate features across scales to promote information flow. Two key ingredients of GXN include a novel vertex infomax …