JuliaDiff / JuliaDiff/ChainRules.jl
Backpropagation-Friendly Eigendecomposition
Open
Nobody has claimed this yet.
enhancement
help wanted
- Dominant language
- Julia
- Stars
- 475
- Forks
- 98
- PR merge metrics
- No merged PRs in 30d
Description
Not really just a new rule, just a better one?
https://papers.nips.cc/paper/8579-backpropagation-friendly-eigendecomposition.pdf
Contributor guide
No contributing guide indexed for this repository
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 reading the linked NeurIPS paper and comparing its backpropagation-friendly eigendecomposition approach with the existing ChainRules.jl coverage. Clarify the intended API, mathematical behavior, and validation cases before implementation; done means an agreed rule that is implemented and validated in the repository.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100