JuliaDiff / JuliaDiff/DifferentiationInterface.jl
Use Jacobian of gradient for Hessian
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core
- Dominant language
- Julia
- Stars
- 313
- Forks
- 35
- PR merge metrics
- No merged PRs in 30d
Description
Right now, HVPs are computed individually and assembled, but this was only useful for the sparse case
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the code that computes HVPs individually and assembles them, as described in the issue. Determine how the Jacobian of the gradient should replace that path while retaining the sparse-case behavior; done means Hessian computation uses the proposed approach and existing behavior remains covered.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100