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rnn: Recurrent Neural Network

Implementation of a Recurrent Neural Network architectures in native R, including Long Short-Term Memory (Hochreiter and Schmidhuber, <doi:10.1162/neco.1997.9.8.1735>), Gated Recurrent Unit (Chung et al., <doi:10.48550/arXiv.1412.3555>) and vanilla RNN.

Version:1.9.0
Depends:R (≥ 3.2.2)
Imports:attention,sigmoid (≥ 1.4.0)
Suggests:testthat,knitr,rmarkdown
Published:2023-04-22
DOI:10.32614/CRAN.package.rnn
Author:Bastiaan QuastORCID iD [aut, cre]
Maintainer:Bastiaan Quast <bquast at gmail.com>
BugReports:https://github.com/bquast/rnn/issues
License:GPL-3
URL:https://qua.st/rnn/,https://github.com/bquast/rnn
NeedsCompilation:no
Citation:rnn citation info
Materials:README,NEWS
CRAN checks:rnn results

Documentation:

Reference manual:rnn.html ,rnn.pdf
Vignettes:GRU units (source,R code)
LSTM units (source,R code)
Basic Recurrent Neural Network (source,R code)
Recurrent Neural Network (source,R code)
RNN units (source,R code)
Simple Self-Attention from Scratch (source,R code)
Sinus and Cosinus (source,R code)

Downloads:

Package source: rnn_1.9.0.tar.gz
Windows binaries: r-devel:rnn_1.9.0.zip, r-release:rnn_1.9.0.zip, r-oldrel:rnn_1.9.0.zip
macOS binaries: r-release (arm64):rnn_1.9.0.tgz, r-oldrel (arm64):rnn_1.9.0.tgz, r-release (x86_64):rnn_1.9.0.tgz, r-oldrel (x86_64):rnn_1.9.0.tgz
Old sources: rnn archive

Reverse dependencies:

Reverse imports:SLBDD

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=rnnto link to this page.


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