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nnR
View on CRAN: Click
here
Download and install nnR package within the R console
Install from CRAN:
install.packages("nnR")
Install from Github:
library("remotes")
install_github("cran/nnR")
Install by package version:
library("remotes")
install_version("nnR", "0.1.0")
Attach the package and use:
library("nnR")
Maintained by
Shakil Rafi
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.nnR . https://github.com/2shakilrafi/nnR/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc . https://github.com/2shakilrafi/nnR/ . nnR results . nnR.pdf . nnR . nnR_0.1.0.tar.gz . nnR_0.1.0.zip . nnR_0.1.0.zip . nnR_0.1.0.zip . nnR_0.1.0.tgz . nnR_0.1.0.tgz . nnR_0.1.0.tgz . nnR_0.1.0.tgz . nnR_0.1.0.tgz . nnR_0.1.0.tgz . https://CRAN.R-project.org/package=nnR .
First Published: 2024-02-14
Latest Update: 2024-02-14
Description:
Do algebraic operations on neural networks. We seek here to implement
in R, operations on neural networks and their resulting approximations. Our operations derive
their descriptions mainly from
Rafi S., Padgett, J.L., and Nakarmi, U. (2024), "Towards an Algebraic Framework For Approximating Functions Using Neural Network Polynomials", ,
Grohs P., Hornung, F., Jentzen, A. et al. (2023), "Space-time error estimates for deep neural network approximations for differential equations", ,
Jentzen A., Kuckuck B., von Wurstemberger, P. (2023), "Mathematical Introduction to Deep Learning Methods, Implementations, and Theory" .
Our implementation is meant mainly as a pedagogical tool, and proof of concept. Faster implementations with
deeper vectorizations may be made in future versions.
How to cite:
Shakil Rafi (2024). nnR: Neural Networks Made Algebraic. R package version 0.1.0, https://cran.r-project.org/web/packages/nnR. Accessed 17 Feb. 2025.
Previous versions and publish date:
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