https://github.com/NFFT/ANOVAapprox.jl

Approximation Package for High-Dimensional Functions in Julia
https://github.com/NFFT/ANOVAapprox.jl

approximation julia

Last synced: 3 months ago
JSON representation

Approximation Package for High-Dimensional Functions in Julia

• Host: GitHub
• URL: https://github.com/NFFT/ANOVAapprox.jl
• Owner: NFFT
• License: gpl-3.0
• Created: 2020-10-09T07:48:22.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2024-06-01T12:46:07.000Z (5 months ago)
• Last Synced: 2024-06-23T04:56:37.953Z (5 months ago)
• Topics: approximation, julia
• Language: Julia
• Homepage:
• Size: 399 KB
• Stars: 0
• Watchers: 10
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-sciml - NFFT/ANOVAapprox.jl: Approximation Package for High-Dimensional Functions in Julia

README

        
# ANOVAapprox.jl

[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://nfft.github.io/ANOVAapprox.jl/stable)

[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://nfft.github.io/ANOVAapprox.jl/dev)

[![ci](https://github.com/NFFT/ANOVAapprox.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/NFFT/ANOVAapprox.jl/actions?query=workflow%3ACI+branch%3Amain)

[![codecov](https://codecov.io/gh/NFFT/ANOVAapprox.jl/branch/main/graph/badge.svg?token=5RUDL3Z3S5)](https://codecov.io/gh/NFFT/ANOVAapprox.jl)

[![Aqua QA](https://img.shields.io/badge/Aqua.jl-%F0%9F%8C%A2-aqua.svg)](https://github.com/JuliaTesting/Aqua.jl)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5657976.svg)](https://doi.org/10.5281/zenodo.5657976)

This package provides a framework for the method ANOVAapprox to approximate high-dimensional functions with a low superposition dimension or a sparse ANOVA decomposition from scattered data. The method has been dicussed and applied in the following articles/preprints:



  
D. Potts and M. Schmischke 
 

  Interpretable transformed ANOVA approximation on the example of the prevention of forest fires 


  arXiv, PDF



  
F. Bartel, D. Potts und M. Schmischke 
 

  Grouped transformations and Regularization in high-dimensional explainable ANOVA approximation 


  SIAM Journal on Scientific Computing (accepted) 


  arXiv, PDF



  
D. Potts and M. Schmischke 
 

  Interpretable approximation of high-dimensional data 


  SIAM Journal on Mathematics of Data Science (accepted) 


  arXiv, PDF, Software



  
D. Potts and M. Schmischke 
 

  Learning multivariate functions with low-dimensional structures using polynomial bases


  Journal of Computational and Applied Mathematics 403, 113821, 2021


  DOI, arXiv, PDF



  
D. Potts and M. Schmischke 
 

  Approximation of high-dimensional periodic functions with Fourier-based methods


  SIAM Journal on Numerical Analysis 59 (5), 2393-2429, 2021


  DOI, arXiv, PDF



L. Lippert, D. Potts and T. Ullrich 
 

  Fast Hyperbolic Wavelet Regression meets ANOVA


  ArXiv: 2108.13197


  arXiv, PDF





`ANOVAapprox.jl` provides the following functionality:

- approximation of high-dimensional periodic and nonperiodic functions with a sparse ANOVA decomposition

- analysis tools for interpretability (global sensitvitiy indices, attribute ranking, shapley values)

## Getting started

In Julia you can get started by typing

```julia

] add ANOVAapprox

```

then checkout the [documentation](https://nfft.github.io/ANOVAapprox.jl/stable/).