JuliaGaussianProcesses / JuliaGaussianProcesses/KernelFunctions.jl
Symmetry not used to compute self covariance matrix
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 275
- Forks
- 41
- PR merge metrics
- No merged PRs in 30d
Description
Right now covariance function is computed on every matrix element instead of ~ half of it. This could be improved! cf: https://github.com/theogf/KernelFunctions.jl/blob/9e8dc488cb5f40529be086fcf32954d5471cdf21/src/kernelmatrix.jl#L53
https://github.com/theogf/KernelFunctions.jl/blob/9e8dc488cb5f40529be086fcf32954d5471cdf21/src/kernelmatrix.jl#L15
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 in src/kernelmatrix.jl at the referenced lines 15 and 53, and trace how the self-covariance matrix is assembled. Confirm where symmetry permits reusing entries, then verify that the resulting matrix is unchanged while avoiding duplicate covariance evaluations.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning, performance
- Issue type
- Refactor
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100