tfNeuralODE: Create Neural Ordinary Differential Equations with 'tensorflow'

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
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

Documentation:

Reference manual: tfNeuralODE.pdf
Vignettes: tfNeuralODE-Adjoint
tfNeuralODE-Spirals

Downloads:

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

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