Eva Feng

The Correspondence Between Bounded Graph Neural Networks and Fragments of First-Order Logic

Graph Neural Networks (GNNs) address two key challenges in applying deep learning to graph-structured data: they handle varying size input graphs and ensure invariance under graph isomorphism. While GNNs have demonstrated broad applicability, understanding their expressive power remains an important