Learning Prioritized Node-Wise Message Propagation in Graph Neural Networks (Extended Abstract)

Graphs are ubiquitous in the real world, in graphs, nodes represent entities and edges capture their relationships. Recently, graph neural networks (GNNs) [3]–[6] have been proposed to integrate these two sources of information. In GNNs, a node's embedding is learned by aggregating messages from its neighbors.