JuliaGaussianProcesses / JuliaGaussianProcesses/KernelFunctions.jl
Question on `ScaledKernel`
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- Dominant language
- Julia
- Stars
- 275
- Forks
- 41
- PR merge metrics
- No merged PRs in 30d
Description
What is the advantage/use case of using a vector for the variance here?
https://github.com/JuliaGaussianProcesses/KernelFunctions.jl/blob/1831cc6d90276c906db99eaaa265920da68b5b1a/src/kernels/scaledkernel.jl#L14-L22
It seems to me that the allocations just hurt performance without any benefit.
Shall we get rid of it?
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 reading src/kernels/scaledkernel.jl at lines 14–22 and inspect how ScaledKernel's variance vector is used elsewhere in the package. Determine whether the vector supports a documented use case or only adds allocations; done means reaching a project-backed decision on retaining or removing it, with performance behavior checked.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning, performance
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100