Learning Graph Structures With Autoregressive Graph Signal Models
This paper presents a novel approach to graph learning, GL-AR, which leverages estimated autoregressive coefficients to recover undirected graph structures from time-series graph signals with propagation delay. GL-AR can discern graph structures where propagation between vertices is delayed, mirrori...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Open Journal of Signal Processing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11078159/ |
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