Renyuan Ma

A Generative Model for Controllable Feature Heterophily in Graphs

We introduce a principled generative framework for graph signals that enables explicit control of feature heterophily, a key property underlying the effectiveness of graph learning methods. Our model combines a Lipschitz graphon-based random graph generator with Gaussian node features filtered throu…