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Julia package for kernel functions for machine learning

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We have decent enough interface tests in this package, but we don't have good choices for test fakes. See [this blog](https://invenia.github.io/blog/2020/11/06/interfacetesting/) for a description of what they are / why...

This pull request changes the compat entry for the `Functors` package from `0.2` to `0.2, 0.3` for package test. This keeps the compat entries for earlier versions. Note: I have...

This pull request changes the compat entry for the `Functors` package from `0.1, 0.2` to `0.1, 0.2, 0.3`. This keeps the compat entries for earlier versions. Note: I have not...

**Summary** This is an attempt to patch #458. Since this is probably some deeper Julia type inference issue, this solution is likely to be temporary. **Proposed changes** For now, I...

```julia using KernelFunctions using Test k = RBFKernel() + RBFKernel() * ExponentialKernel() @inferred k(0.1, 0.2) # ERROR @time k(0.1, 0.2) # 0.000009 seconds (5 allocations: 176 bytes) ``` but e.g....

I couldn't find an existing issue so I open a new one here. The ColVecs/RowVecs abstraction would be useful in other packages as well that otherwise don't want or need...

Again, curious to see what breaks

https://github.com/JuliaGaussianProcesses/KernelFunctions.jl/pull/425 makes it possible to AD through the `MaternKernel` by dropping the derivative w.r.t. `\nu`. We tried ensuring that it returns a `NotImplemented`, but Zygote doesn't appear to handle it...

Curious to see what breaks...