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Provides a framework for the creation and use of Neural ordinary differential equations with the 'tensorflow' and 'keras' packages. The idea of Neural ordinary differential equations comes from Chen et al. (2018) <doi:10.48550/arXiv.1806.07366>, and presents a novel way of learning and solving differential systems.
Version: | 0.1.0 |
Imports: | tensorflow, keras, reticulate, deSolve |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2023-10-16 |
DOI: | 10.32614/CRAN.package.tfNeuralODE |
Author: | Shayaan Emran [aut, cre, cph] |
Maintainer: | Shayaan Emran <shayaan.emran at gmail.com> |
BugReports: | https://github.com/semran9/tfNeuralODE/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/semran9/tfNeuralODE |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | tfNeuralODE results |
Reference manual: | tfNeuralODE.pdf |
Vignettes: |
tfNeuralODE-Adjoint tfNeuralODE-Spirals |
Package source: | tfNeuralODE_0.1.0.tar.gz |
Windows binaries: | r-devel: tfNeuralODE_0.1.0.zip, r-release: tfNeuralODE_0.1.0.zip, r-oldrel: tfNeuralODE_0.1.0.zip |
macOS binaries: | r-release (arm64): tfNeuralODE_0.1.0.tgz, r-oldrel (arm64): tfNeuralODE_0.1.0.tgz, r-release (x86_64): tfNeuralODE_0.1.0.tgz, r-oldrel (x86_64): tfNeuralODE_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.