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rkaf: Kolmogorov-Arnold Fourier Networks in R

Provides an R implementation of Kolmogorov-Arnold Fourier Networks using the torch backend. The package supports regression, binary classification, multiclass classification, formula and matrix interfaces, mini-batch training, validation splits, early stopping, standardization, best-model restoration, and KAF-specific diagnostics.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: stats, graphics, torch
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, pkgdown
Published: 2026-04-28
DOI: 10.32614/CRAN.package.rkaf
Author: Guillaume Sidoine [aut, cre]
Maintainer: Guillaume Sidoine <gjh.sidoine at gmail.com>
BugReports: https://github.com/gsidoine/rkaf/issues
License: MIT + file LICENSE
URL: https://github.com/gsidoine/rkaf, https://gsidoine.github.io/rkaf/
NeedsCompilation: no
Citation: rkaf citation info
Materials: README, NEWS
CRAN checks: rkaf results

Documentation:

Reference manual: rkaf.html , rkaf.pdf
Vignettes: Getting started with rkaf (source, R code)

Downloads:

Package source: rkaf_0.1.0.tar.gz
Windows binaries: r-devel: rkaf_0.1.0.zip, r-release: rkaf_0.1.0.zip, r-oldrel: rkaf_0.1.0.zip
macOS binaries: r-release (arm64): rkaf_0.1.0.tgz, r-oldrel (arm64): rkaf_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rkaf to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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