-
Notifications
You must be signed in to change notification settings - Fork 9
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Adding support for ODE differentiation and interface for DifferentialEquations.jl #89
Comments
Hi, Sure! This would be very helpful, and really appreciate your pull request. In addition to adding code to I will start to move the examples to documentations, but in the mean time feel free to start your work! |
That is great! Yes, I was planning to also provide with an example we can include in the documentation. I may need some feedback on specific TaylorDiff or SciML generic styles, which I am happy to provide. All this to say that I am sure there will be changes to make to my original PR, which I am looking for ;) |
Sure! Don't worry too much about styles at the beginning, we can definitely refine after examples are up and running. |
Hi, I just moved an example from In addition, I also cleaned up a script https://github.com/JuliaDiff/TaylorDiff.jl/blob/main/examples/integration.jl which I initially wrote in the last year to demonstrate how to use TaylorDiff.jl to compute jet coefficients for Taylor integration. I didn't go further to make it fully functional, but you can use it as a starting point to implement your solver! |
Chris mentioned to me today that you are working on a review paper that will use higher-order autodiff to show several things. Let me know if there's anything specific I can help. In addition, I will also prepare a paper on the implementation and applications of TaylorDiff.jl early next year, and by then we can also collaborate |
Hi!
I had been playing around with using
TaylorDiff.jl
for higher-order differentiation of numerical solutions of ODEs. I have a simple implementation of the method introduced in Appendix D in Taylor-Mode Automatic Differentiation forHigher-Order Derivatives in JAX together with some simple examples of ODEs. I think this quite add some value to the library, since it is particularly important to compute higher-order derivatives of solutions of differential equations for some very specific applications.
I would be happy to make a PR with this, probably into a new module
ode.jl
. Would this be useful for the library? I would love to contribute :)The text was updated successfully, but these errors were encountered: