A Convergence Analysis of Gradient Descent on Graph Neural Networks

We provide a convergence analysis of gradient descent on graph neural networks. Motivation • We consider two settings • ReLU GNNs with one round of message passing. • Linear GNNs with multiple rounds of message passing.