Vaibhav Kumar Dixit

Wrap HyperHessians.jl as an AD backend

4

Though it only focuses on hessians, combining with a gradient call from another package and hessian from https://github.com/KristofferC/HyperHessians.jl would be interesting for second order methods.

Realised due to #209

Tutorials in docs

2

The docs don't have any tutorials, for a start we should just add the test there and iterate from there.

Expand docstrings

1

We should have verbose docstrings and more examples in the Readme to get users to start shifting to using the package.

Possible regression in Turing integration

2

The CI seems to be taking unreasonably long to run through the turing_inference tests, probably something changed in newer releases. Should get bisected and reported

Use updated `build_function`

3

Looks like Symbolics has deprecated use of `build_function(

Would make it easier for users to parse and write them

AMAGOLD support

1

Came across http://proceedings.mlr.press/v108/zhang20e.html which seems to guarantee asymptotic convergence with the goodness of efficiency with SGHMC. Adding here to see if there is interest from users or plans from the...

Curious regarding 0.7 upgrade?

3

Hey, I was wondering what your timeline is for upgrading Mamba.jl to v0.7. Thanks!