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tfNeuralODE  

Create Neural Ordinary Differential Equations with 'tensorflow'
View on CRAN: Click here


Download and install tfNeuralODE package within the R console
Install from CRAN:
install.packages("tfNeuralODE")

Install from Github:
library("remotes")
install_github("cran/tfNeuralODE")

Install by package version:
library("remotes")
install_version("tfNeuralODE", "0.1.0")



Attach the package and use:
library("tfNeuralODE")
Maintained by
Shayaan Emran
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-10-16
Latest Update: 2023-10-16
Description:
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.
How to cite:
Shayaan Emran (2023). tfNeuralODE: Create Neural Ordinary Differential Equations with 'tensorflow'. R package version 0.1.0, https://cran.r-project.org/web/packages/tfNeuralODE. Accessed 05 Jun. 2026.
Previous versions and publish date:
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Complete documentation for tfNeuralODE
Functions, R codes and Examples using the tfNeuralODE R package
Some associated functions: backward . backward_dynamics . euler_step . euler_update . forward . rk4_step . rk4_step_backwards . 
Some associated R codes: eulermethod.R . global.R . neuralODE.R . rk4.R .  Full tfNeuralODE package functions and examples
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