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 Quast ORCID 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.pdf
Vignettes: GRU units
LSTM units
Basic Recurrent Neural Network
Recurrent Neural Network
RNN units
Simple Self-Attention from Scratch
Sinus and Cosinus

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:

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