Reversible and irreversible bracket-based dynamics for deep graph neural networks

Anthony Gruber, Kookjin Lee, Nathaniel Trask

Recent works have shown that physics-inspired architectures allow the training of deep graph neural networks (GNNs) without oversmoothing. The role of these physics is unclear, how…