How a wise use of direction when doing message passing on heterophilic graphs can result in very significant gains. — Graph Neural Networks (GNNs) are highly effective at modelling relational data. However, current GNN models frequently assume the input graph to be undirected, overlooking the inherent directionality of many real-world graphs, such as social, transportation, transaction, and citation networks. In this blog post, we explore the impact of edge directionality…