An adaptive residual sub-sampling algorithm for kernel interpolation based on maximum likelihood estimations

DOI10.1016/j.cam.2022.114658zbMath1497.65018OpenAlexW4289745762WikidataQ113878682 ScholiaQ113878682MaRDI QIDQ2088806

Alessandra De Rossi, Roberto Cavoretto

Publication date: 6 October 2022

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2022.114658

zbMATH Keywords

radial basis functionsadaptive algorithmsmeshless interpolationoptimal shape parametersresidual sub-sampling methods

Mathematics Subject Classification ID

Numerical interpolation (65D05) Algorithms for approximation of functions (65D15) Numerical radial basis function approximation (65D12)

Related Items (3)

Adaptive residual Refinement in an RBF Finite difference scheme for 2D time-dependent problems ⋮ Learning with partition of unity-based kriging estimators ⋮ Adaptive selection strategy of shape parameters for LRBF for solving partial differential equations

Uses Software

• Matlab
• GaussQR
• RBFCUB

Cites Work

• Unnamed Item
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• Radial Basis Functions
• Scattered Data Approximation

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