Abstract: Graph Neural Networks (GNNs) are effective and popular techniques for representation learning of graph data, significantly relying on message passing mechanism. Most GNNs utilize graph ...

Abstract: We propose a novel factor model in the graph frequency domain for multivariate data residing on the vertices of a graph, referred to as a multivariate graph signal. By utilizing graph ...