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Node-bound communities for partition of unity interpolation on graphs

Author

Listed:
  • Cavoretto, Roberto
  • De Rossi, Alessandra
  • Lancellotti, Sandro
  • Romaniello, Federico

Abstract

Graph signal processing benefits significantly from the direct and highly adaptable supplementary techniques offered by partition of unity methods (PUMs) on graphs. In our approach, we demonstrate the generation of a partition of unity solely based on the underlying graph structure, employing an algorithm that relies exclusively on centrality measures and modularity, without requiring the input of the number of subdomains. Subsequently, we integrate PUMs with a local graph basis function (GBF) approximation method to develop cost-effective global interpolation schemes. We also discuss numerical experiments conducted on both synthetic and real datasets to assess the performance of this presented technique.

Suggested Citation

  • Cavoretto, Roberto & De Rossi, Alessandra & Lancellotti, Sandro & Romaniello, Federico, 2024. "Node-bound communities for partition of unity interpolation on graphs," Applied Mathematics and Computation, Elsevier, vol. 467(C).
    • Handle: RePEc:eee:apmaco:v:467:y:2024:i:c:s0096300323006719
    DOI: 10.1016/j.amc.2023.128502
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    References listed on IDEAS

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    1. Cavoretto, Roberto & De Rossi, Alessandra, 2020. "Error indicators and refinement strategies for solving Poisson problems through a RBF partition of unity collocation scheme," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    2. Cavoretto, R. & De Rossi, A. & Perracchione, E., 2023. "Learning with Partition of Unity-based Kriging Estimators," Applied Mathematics and Computation, Elsevier, vol. 448(C).
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