We propose an efficient algorithm for graph matching based on similarity scores constructed
from counting a certain family of weighted trees rooted at each vertex. For two Erdős–Rényi …

This paper studies the problem of recovering the hidden vertex correspondence between
two edge-correlated random graphs. We focus on the Gaussian model where the two graphs …

Random graph matching refers to recovering the underlying vertex correspondence
between two random graphs with correlated edges; a prominent example is when the two …

We consider the task of learning latent community structure from multiple correlated
networks. First, we study the problem of learning the latent vertex correspondence between …

Graph matching, also known as network alignment, aims at recovering the latent vertex
correspondence between two unlabeled, edge-correlated weighted graphs. To tackle this …

This paper deals with the problem of graph matching or network alignment for Erdős–Rényi
graphs, which can be viewed as a noisy average-case version of the graph isomorphism …

Matching recovery threshold for correlated random graphs Page 1 The Annals of Statistics
2023, Vol. 51, No. 4, 1718–1743 https://doi.org/10.1214/23-AOS2305 © Institute of …

We study a noisy graph isomorphism problem, where the goal is to perfectly recover the
vertex correspondence between two edge‐correlated graphs, with an initial seed set of …

In this paper, we consider the graph alignment problem, which is the problem of recovering,
given two graphs, a one-to-one map** between nodes that maximizes edge overlap. This …

We study the graph alignment problem over two independent Erd\H {o} sR\'enyi graphs on $
n $ vertices, with edge density $ p $ falling into two regimes separated by the critical window …