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Julia package for kernel functions for machine learning

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## Introduction: How would you simulate gradients If you want to simulate the gradient of a random function $Z$, it turns out that you simply need to take derivatives of...

Following this [discourse discussion](https://discourse.julialang.org/t/gps-sum-of-independent-kernels/98542). 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'...

enhancement

To agree with our style guide, we should have underscores separating words (snake_case), and `kernelmatrix` (as well as other functions) should follow this rule

Testing locally on 1.8.5, I find that https://github.com/JuliaGaussianProcesses/KernelFunctions.jl/blob/master/test/mokernels/independent.jl#L17 occasionally fails, ```Julia independent: Test Failed at .../KernelFunctions.jl/test/mokernels/independent.jl:17 Expression: kernelmatrix(k, x, y) == kernelmatrix(k, collect(x), collect(y)) Evaluated: [0.6308251776147069 0.7710805544766418 … 0.0 0.0;...

It would be nice to define `isequal` and/or `==` as widely as possible between `Kernel`s and `Transform`s. At the moment some basic cases seem to be missing, such as ```Julia...

Hi All, Thanks for the wonderful package. I'm just starting to explore the source code. I was curious about a very small decision. If I do: ```julia k = SqExponentialKernel()...

Bumps [dawidd6/action-download-artifact](https://github.com/dawidd6/action-download-artifact) from 9 to 11. Release notes Sourced from dawidd6/action-download-artifact's releases. v11 Full Changelog: https://github.com/dawidd6/action-download-artifact/compare/v10...v11 v10 What's Changed Fix the download-commit test to actually look for a commit by...

dependencies
github_actions

julia> versioninfo() Julia Version 1.11.5 Commit 760b2e5b73 (2025-04-14 06:53 UTC) Build Info: Official https://julialang.org/ release Platform Info: OS: Windows (x86_64-w64-mingw32) CPU: 24 × Intel(R) Xeon(R) Silver 4410Y WORD_SIZE: 64 LLVM:...

I have a project in which I take gradients of Matern kernels with respect to an argument via ForwardDiff and was able to do so without issue until recently. When...

The current docs job is failing due to one of the examples erroring: https://github.com/JuliaGaussianProcesses/KernelFunctions.jl/actions/runs/13119973055/job/36603405080#step:5:46 This looks like a simple update to apply

bug
good first issue