We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
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
With efficient fvp and ggnvp #63 it might be nice to add the Hessian-free optimization algorithm of https://www.cs.toronto.edu/~jmartens/docs/Deep_HessianFree.pdf
fvp
ggnvp
This algorithm runs a short conjugate gradient run at each iteration, so it might be worth implementing posteriors.cg similar to the jax version
posteriors.cg
The text was updated successfully, but these errors were encountered:
Conjugate gradient (posteriors.cg) added in #73 🥳
Sorry, something went wrong.
Goal is to have a hessian_free_opt.py module that includes build, init, and update functions similarly to other modules, which uses posteriors.cg.
hessian_free_opt.py
build
init
update
No branches or pull requests
With efficient
fvp
andggnvp
#63 it might be nice to add the Hessian-free optimization algorithm of https://www.cs.toronto.edu/~jmartens/docs/Deep_HessianFree.pdfThis algorithm runs a short conjugate gradient run at each iteration, so it might be worth implementing
posteriors.cg
similar to the jax versionThe text was updated successfully, but these errors were encountered: