Message-Passing GNNs

GNNs struggle to approximate sparse matrix factorizations

A new research paper demonstrates that standard message-passing Graph Neural Networks (GNNs) are fundamentally unable to approximate sparse triangular factorizations. The study shows that even advanced architectures lik…