Beltrami Flow and Neural Diffusion on Graphs

Understand

We propose a novel class of graph neural networks based on the discretised Beltrami flow, a non-Euclidean diffusion PDE.

• In our model, node features are supplemented with positional encodings derived from the graph topology and jointly evolved by the Beltrami flow, producing simultaneously continuous feature learning and topology evolution.
• The resulting model generalises many popular graph neural networks and achieves state-of-the-art results on several benchmarks.