# Multiplex graph matching matched filters

## TL;DR

This paper introduces a multiplex graph matching approach that extends classical methods to handle multi-channel networks, improving template detection in complex background networks through theoretical and empirical validation.

## Contribution

It develops a multiplex analogue of graph matching, enabling efficient template detection in multi-channel networks, which is a novel extension of previous single-channel methods.

## Key findings

- The method effectively detects templates in multiplex networks.
- Considering multiple channels enhances detection accuracy.
- The approach is validated both theoretically and empirically.

## Abstract

We consider the problem of detecting a noisy induced multiplex template network in a larger multiplex background network. Our approach, which extends the framework of Sussman et al. (2019) to the multiplex setting, leverages a multiplex analogue of the classical graph matching problem to use the template as a matched filter for efficiently searching the background for candidate template matches. The effectiveness of our approach is demonstrated both theoretically and empirically, with particular attention paid to the potential benefits of considering multiple channels.