GaussQR: Stable Gaussian computation. Welcome to the GaussQR software website, developed both to facilitate experimentation with positive definite kernels (radial basis functions) and as supplemental content for the new book Kernel-Based Approximation Methods in MATLAB available from World Scientific Press. Although we are always updating our software library, we are happy to announce the release of the GaussQR 2.0 library (previously called RBF-QR) which has a host of brand new examples designed to demonstrate topics in our book. The upgrade should be relatively painless if you have been keeping up with the repository, although some adjustment is needed if you were still running rbfqr-1.3. Please contact us if you have difficulty using this, or if inconsistencies appear.

References in zbMATH (referenced in 98 articles )

Showing results 81 to 98 of 98.
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  1. Cavoretto, R.; De Marchi, S.; De Rossi, A.; Perracchione, E.; Santin, G.: Partition of unity interpolation using stable kernel-based techniques (2017)
  2. De Marchi, Stefano; Idda, Andrea; Santin, Gabriele: A rescaled method for RBF approximation (2017)
  3. Iske, Armin; Le Borne, Sabine; Wende, Michael: Hierarchical matrix approximation for kernel-based scattered data interpolation (2017)
  4. Lenarduzzi, Licia; Schaback, Robert: Kernel-based adaptive approximation of functions with discontinuities (2017)
  5. Liu, Xiao-Yan; Chen, C. S.; Karageorghis, Andreas: Conformal mapping for the efficient solution of Poisson problems with the Kansa-RBF method (2017)
  6. McCourt, Michael; Fasshauer, Gregory E.: Stable likelihood computation for Gaussian random fields (2017)
  7. Mishra, Pankaj K.; Nath, Sankar K.: On the convergence of iterative methods and pseudoinverse approaches in global meshless collocation (2017)
  8. Mishra, Pankaj K.; Nath, Sankar K.; Kosec, Gregor; Sen, Mrinal K.: An improved radial basis-pseudospectral method with hybrid Gaussian-cubic kernels (2017)
  9. Sarra, S.A.: The Matlab Radial Basis Function Toolbox (2017) not zbMATH
  10. Sarra, Scott A.; Cogar, Samuel: An examination of evaluation algorithms for the RBF method (2017)
  11. Ye, Qi: Generalizations of simple kriging methods in spatial data analysis (2017)
  12. Ye, Qi: Kernel-based approximation methods for partial differential equations: deterministic or stochastic problems? (2017)
  13. Cavoretto, Roberto; De Rossi, Alessandra; Perracchione, Emma: Efficient computation of partition of unity interpolants through a block-based searching technique (2016)
  14. Fasshauer, Gregory; McCourt, Michael: Kernel-based approximation methods using MATLAB (2016)
  15. Huang, C.-S.; Hung, C.-H.; Wang, S.: Computing eigenmodes of elliptic operators using increasingly flat radial basis functions (2016)
  16. Jaśkowiec, J.; Milewski, S.: Coupling finite element method with meshless finite difference method in thermomechanical problems (2016)
  17. Ling, Leevan: A fast block-greedy algorithm for quasi-optimal meshless trial subspace selection (2016)
  18. Rashidinia, J.; Fasshauer, G. E.; Khasi, M.: A stable method for the evaluation of Gaussian radial basis function solutions of interpolation and collocation problems (2016)

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