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nnR  

Neural Networks Made Algebraic
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]
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 01 Apr. 2025.
Previous versions and publish date:
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Complete documentation for nnR
Functions, R codes and Examples using the nnR R package
Full nnR package functions and examples
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