4 papers
Thresholded Local Hyper-Flow Diffusion
Meher Chaitanya, Sebastian Dalleiger, Luana Ruiz
Local Hyper-Flow Diffusion (HFD) gives an edge-size-independent Cheeger-type guarantee for seeded clustering in general submodular hypergraphs, but existing HFD solvers do not keep…
Graph Cascades: Contagion-Based Mesoscopic Rewiring for Structure-Aware Graph Machine Learning
Meher Chaitanya, My Le, Luana Ruiz
We introduce Graph Cascades, a mesoscopic rewiring strategy for Graph Neural Networks (GNNs) and Graph Transformers (GTs) that captures intermediate-scale graph structure beyond pu…
Dirichlet Meets Horvitz and Thompson: Estimating Homophily in Large Networks via Sampling
Hamed Ajorlou, Gonzalo Mateos, Luana Ruiz
Assessing homophily in large-scale networks is central to understanding structural regularities in graphs, and thus inform the choice of models (such as graph neural networks) adop…
A Generative Model for Controllable Feature Heterophily in Graphs
Haoyu Wang, Renyuan Ma, Gonzalo Mateos +1
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…