2023
$\mathscr{N}$-WL: A New Hierarchy of Expressivity for Graph Neural Networks
ICLR 2023poster
The expressive power of Graph Neural Networks (GNNs) is fundamental for understanding their capabilities and limitations, i.e., what graph properties can or cannot be learnt by a GNN. Since standard GNNs have been characterised to be upper-bounded by the Weisfeiler-Lehman (1-WL) algorithm, recent a…