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Reports and tools

 

spatfGPs python and R packages (link to the website https://github.com/anfelopera/spatfGPs )

  • spatfGP aims at building metamodels for cases where correlated spatial outputs (e.g. flood events) are driven by multiple functional inputs (e.g. hydro-meteorological conditions). Codes are based on the paper ``Multi-output Gaussian processes with functional data: A study on coastal flood hazard assessment'' (link to the paper: https://arxiv.org/abs/2007.14052)
  • The repository provides Python and R codes based on the GPflow library and the kergp package (respectively)
  • Betancourt, J., Bachoc, F., Klein, T., Gamboa, F. (2020). Technical Report: Ant Colony Based Model Selection for Functional-Input Gaussian Process Regression. Ref. D3.b (WP3.2), RISCOPE project. [Open access version]
  • funGp R package [website]
    • Online releases: [GitHub], [CRAN].
    • User manual: Betancourt, J., Bachoc, F., Klein, T. (2020). R Package Manual: Gaussian Process Regression for Scalar and Functional Inputs with funGp - The in-depth tour. RISCOPE project.
    • Betancourt J., Bachoc F., Klein T., Idier D., Rohmer J., Deville Y. (2024) funGp: An R Package for Gaussian Process Regression with Scalar and Functional InputsJournal of Statistical Software, 109(5), 1–51. [POV
 
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