FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network

Researchers introduce FSW-GNN, the first Message Passing Neural Network that is fully bi-Lipschitz with respect to standard WL-equivalent graph metrics. This addresses the limitation where standard MPNNs produce poorly distinguishable outputs for separable graphs, with empirical results showing competitive performance and superior accuracy in long-range tasks.