Abstract: Graph topology inference is a significant task in many application domains. Existing approaches are mostly limited to learning a single graph assuming that the observed data is homogeneous.

Abstract: Graph Convolutional Networks (GCNs) have been widely studied for semi-supervised learning tasks. It is known that the graph convolution operations in most of existing GCNs are composed of ...