Skip to content

dlinzner-bcs/min_neuralODEs

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

min_neuralODEs

An absolute minimum (inefficient) implementation for learning neuralODEs using the adjoint method. Warning: For educational purposes only!

[1] Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud. "Neural Ordinary Differential Equations." Advances in Neural Processing Information Systems. 2018. [arxiv]

[2] Calver, J., & Enright, W. "Numerical methods for computing sensitivities for ODEs and DDEs." Numerical Algorithms, 74(4), 1101–1117 2017.

About

An absolute minimum implementation for learning neuralODEs using the adjoint method. Warning: For educational purposes only!

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages