Graph Diffusion Spread Bounds Using Laplacian Regularisation

Researchers gave a closed‑form upper bound on graph diffusion spread: one term set by the graph’s max node degree, another shrinking with regularisation strength (inverse‑square‑root). getnews.me/graph-diffusion-spread-b... #graphdiffusion #laplacian

Riemannian Graph Diffusion Framework Boosts Generation and Prediction

GeoMancer swaps exponential mapping for a gyrokernel and separates node, edge, embeddings, improving generation and prediction on molecular, social and citation benchmarks. Read more: getnews.me/riemannian-graph-diffusi... #geomancer #graphdiffusion

New Graph Diffusion Model Simulates Early Brain Development

A graph‑diffusion network trained on dHCP data can simulate cortical development, achieving a prediction accuracy of 0.85 ± 0.62 and fooling an age‑regression model. getnews.me/new-graph-diffusion-mode... #graphdiffusion #neuroscience #dhcp