Exploration of kernel parameters in signal GBF-PUM approximation on graphs
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Publication:6592300
DOI10.2478/CAIM-2024-0004zbMATH Open1545.65058MaRDI QIDQ6592300
Roberto Cavoretto, S. Mereu, Alessandra De Rossi
Publication date: 26 August 2024
Published in: Communications in Applied and Industrial Mathematics (Search for Journal in Brave)
kernel methodsapproximation algorithmspartition of unity methodsgraph basis functionsgraph interpolation
Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Numerical interpolation (65D05) Interpolation in approximation theory (41A05)
Cites Work
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- Half sampling on bipartite graphs
- Variational splines and Paley-Wiener spaces on Combinatorial graphs
- Interpolating splines on graphs for data science applications
- Graph signal sampling and interpolation based on clusters and averages
- Stability of kernel-based interpolation
- Clustering to minimize the maximum intercluster distance
- Partition of unity methods for signal processing on graphs
- Graph signal interpolation with positive definite graph basis functions
- Partition of unity interpolation using stable kernel-based techniques
- Sampling in Paley-Wiener spaces on combinatorial graphs
- A Best Possible Heuristic for the k-Center Problem
- Matrix Analysis
- Local-Set-Based Graph Signal Reconstruction
- Kernel-Based Reconstruction of Graph Signals
- Shapes of Uncertainty in Spectral Graph Theory
- Theory of Reproducing Kernels
- Networks
- Node-bound communities for partition of unity interpolation on graphs
- GBFPUM -- a MATLAB package for partition of unity based signal interpolation and approximation on graphs
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