Graph Canonical Coherence Analysis

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Kim, Kyusoon, Oh, Hee-Seok
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866908763538063360
author Kim, Kyusoon
Oh, Hee-Seok
author_facet Kim, Kyusoon
Oh, Hee-Seok
contents We propose graph canonical coherence analysis (gCChA), a novel framework that extends canonical correlation analysis to multivariate graph signals in the graph frequency domain. The proposed method addresses challenges posed by the inherent features of graphs: discreteness, finiteness, and irregularity. It identifies pairs of canonical graph signals that maximize their coherence, enabling the exploration of relationships between two sets of graph signals from a spectral perspective. This framework shows how these relationships change across different structural scales of the graph. We demonstrate the usefulness of this method through applications to economic and energy datasets of G20 countries and the USPS handwritten digit dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2601_09038
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Graph Canonical Coherence Analysis
Kim, Kyusoon
Oh, Hee-Seok
Methodology
We propose graph canonical coherence analysis (gCChA), a novel framework that extends canonical correlation analysis to multivariate graph signals in the graph frequency domain. The proposed method addresses challenges posed by the inherent features of graphs: discreteness, finiteness, and irregularity. It identifies pairs of canonical graph signals that maximize their coherence, enabling the exploration of relationships between two sets of graph signals from a spectral perspective. This framework shows how these relationships change across different structural scales of the graph. We demonstrate the usefulness of this method through applications to economic and energy datasets of G20 countries and the USPS handwritten digit dataset.
title Graph Canonical Coherence Analysis
topic Methodology
url https://arxiv.org/abs/2601.09038