Simon Heilig

Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks

The dynamics of information diffusion within graphs is a critical open issue that heavily influences graph representation learning, especially when considering long-range propagation. This calls for principled approaches that control and regulate the degree of propagation and dissipation of informat…