Graph Neural Networks with Local Graph Parameters

1 code implementation • NeurIPS 2021 • Pablo Barceló, Floris Geerts, Juan Reutter, Maksimilian Ryschkov

We propose local graph parameter enabled GNNs as a framework for studying the latter kind of approaches and precisely characterize their distinguishing power, in terms of a variant of the WL test, and in terms of the graph structural properties that they can take into account.

Graph Learning