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Implementation of 'BayesFlux.jl' for R; It extends the famous 'Flux.jl' machine learning library to Bayesian Neural Networks. The goal is not to have the fastest production ready library, but rather to allow more people to be able to use and research on Bayesian Neural Networks.
| Version: | 0.1.3 |
| Imports: | JuliaCall (≥ 0.17.5), stats |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2023-12-10 |
| DOI: | 10.32614/CRAN.package.BayesFluxR |
| Author: | Enrico Wegner [aut, cre] |
| Maintainer: | Enrico Wegner <e.wegner at student.maastrichtuniversity.nl> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | BayesFluxR results |
| Reference manual: | BayesFluxR.pdf |
| Package source: | BayesFluxR_0.1.3.tar.gz |
| Windows binaries: | r-devel: BayesFluxR_0.1.3.zip, r-release: BayesFluxR_0.1.3.zip, r-oldrel: BayesFluxR_0.1.3.zip |
| macOS binaries: | r-release (arm64): BayesFluxR_0.1.3.tgz, r-oldrel (arm64): BayesFluxR_0.1.3.tgz, r-release (x86_64): BayesFluxR_0.1.3.tgz, r-oldrel (x86_64): BayesFluxR_0.1.3.tgz |
| Old sources: | BayesFluxR archive |
Please use the canonical form https://CRAN.R-project.org/package=BayesFluxR 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.