Sharp Statistical Thresholds for Attributed Gaussian Graph Matching
The study investigates matching networks where both edge weights and node features are correlated using a Gaussian model. It derives precise information-theoretic thresholds for exact, almost exact, and partial recovery of the underlying alignment. A key finding is that contextual information creates a richer structure where the thresholds for exact and almost exact recovery do not coincide.