JuliaGaussianProcesses / JuliaGaussianProcesses/KernelFunctions.jl
Sum of independent kernels
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- Dominant language
- Julia
- Stars
- 275
- Forks
- 41
- PR merge metrics
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Description
Following this discourse discussion. Currently, there is no building block to sum independent Kernels, analog to KernelTensorProduct but with addition instead of multiplication:
For inputs $x = (x_1,\dots,x_n)$ and $x' = (x_1',\dots,x_n')$, the independent sum of kernels $k_1, \dots, k_n$:
$$ k(x, x'; k_1, \dots k_n) = \sum_{i=1}^n k_i(x_i, x_i') $$
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 with the existing KernelTensorProduct building block and review the linked Discourse discussion for the intended behavior of independent kernel sums. Define the corresponding sum-of-kernels abstraction for inputs split into independent components, and verify that it computes the stated sum of k_i(x_i, x_i').
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100