GaussQR

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 41 to 60 of 98.
Sorted by year (citations)
  1. Soradi-Zeid, Samaneh: Efficient radial basis functions approaches for solving a class of fractional optimal control problems (2020)
  2. Tanaka, Ken’ichiro: Generation of point sets by convex optimization for interpolation in reproducing kernel Hilbert spaces (2020)
  3. Uddin, Marjan; Ali, Hazrat: Space-time kernel based numerical method for generalized Black-Scholes equation (2020)
  4. Ahmadvand, M.; Esmaeilbeigi, M.; Kamandi, A.; Yaghoobi, F. M.: A novel hybrid trust region algorithm based on nonmonotone and LOOCV techniques (2019)
  5. Ahmadvand, Mohammad; Esmaeilbeigi, Mohsen; Kamandi, Ahmad; Yaghoobi, Farajollah Mohammadi: An improved hybrid-ORBIT algorithm based on point sorting and MLE technique (2019)
  6. Azarnavid, Babak; Nabati, Mohammad; Emamjome, Mahdi; Parand, Kourosh: Imposing various boundary conditions on positive definite kernels (2019)
  7. Böhmer, Klaus; Schaback, Robert: A meshfree method for solving the Monge-Ampère equation (2019)
  8. Cavoretto, R.; De Rossi, A.: Adaptive meshless refinement schemes for RBF-PUM collocation (2019)
  9. Coroianu, Lucian; Costarelli, Danilo; Gal, Sorin G.; Vinti, Gianluca: The max-product generalized sampling operators: convergence and quantitative estimates (2019)
  10. Crawford, Lorin; Flaxman, Seth R.; Runcie, Daniel E.; West, Mike: Variable prioritization in nonlinear black box methods: a genetic association case study (2019)
  11. De Marchi, S.; Martínez, A.; Perracchione, E.: Fast and stable rational RBF-based partition of unity interpolation (2019)
  12. Esmaeilbeigi, M.; Chatrabgoun, O.; Cheraghi, M.: The role of Hilbert-Schmidt SVD basis in Hermite-Birkhoff interpolation in fractional sense (2019)
  13. Esmaeilbeigi, M.; Chatrabgoun, O.; Shafa, Maryam: Numerical solution of time-dependent stochastic partial differential equations using RBF partition of unity collocation method based on finite difference (2019)
  14. Esmaeilbeigi, Mohsen; Chatrabgoun, Omid: An efficient method based on RBFs for multilayer data interpolation with application in air pollution data analysis (2019)
  15. Karvonen, Toni; Särkkä, Simo: Gaussian kernel quadrature at scaled Gauss-Hermite nodes (2019)
  16. Kormann, Katharina; Lasser, Caroline; Yurova, Anna: Stable interpolation with isotropic and anisotropic Gaussians using Hermite generating function (2019)
  17. Kunc, Oliver; Fritzen, Felix: Generation of energy-minimizing point sets on spheres and their application in mesh-free interpolation and differentiation (2019)
  18. Le Borne, Sabine: Factorization, symmetrization, and truncated transformation of radial basis function-GA stabilized Gaussian radial basis functions (2019)
  19. Li, Siqing; Ling, Leevan; Cheung, Ka Chun: Discrete least-squares radial basis functions approximations (2019)
  20. Mishra, Pankaj K.; Fasshauer, Gregory E.; Sen, Mrinal K.; Ling, Leevan: A stabilized radial basis-finite difference (RBF-FD) method with hybrid kernels (2019)