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., <arXiv:1412.3555>) and vanilla RNN.
Version: | 0.9.8 |
Depends: | R (≥ 3.2.2) |
Imports: | sigmoid, shiny |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2019-05-27 |
Author: | Bastiaan Quast [aut, cre], Dimitri Fichou [aut] |
Maintainer: | Bastiaan Quast <bquast at gmail.com> |
BugReports: | https://github.com/bquast/rnn/issues |
License: | GPL-3 |
URL: | http://qua.st/rnn, https://github.com/bquast/rnn |
NeedsCompilation: | no |
Citation: | rnn citation info |
Materials: | README NEWS |
CRAN checks: | rnn results |
Reference manual: | rnn.pdf |
Vignettes: |
GRU units LSTM units Basic Recurrent Neural Network Recurrent Neural Network RNN units Sinus and Cosinus |
Package source: | rnn_0.9.8.tar.gz |
Windows binaries: | r-devel: rnn_0.9.8.zip, r-devel-gcc8: rnn_0.9.8.zip, r-release: rnn_0.9.8.zip, r-oldrel: rnn_0.9.8.zip |
OS X binaries: | r-release: rnn_0.9.8.tgz, r-oldrel: rnn_0.9.8.tgz |
Old sources: | rnn archive |
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