Kaan Öcal

If I'm correct now Stheno relies on AbstractGPs instead of providing its own implementation, is that correct? I would propose updating the GP comparison page in that case - having...

I would be open to trying that actually, I have some experience with Bayesian Optimisation although I am (as mentioned) less familiar with the modern Julia way of doing things....

I think for now we might need to rebuild the GP after each training step. This is quite expensive, but one could provide more efficient implementations later on. In any...

Although GalacticOptim has Flux and Optim as two rather large dependencies...

Some initial thoughts about the current AbstractGP API after a bit of experimentation: - There seems to be no simple way of accessing observations in a PosteriorGP except via data.x...

Since I'm planning to move some of my existing GP stuff to Julia I'd love to hear if there's any way I could help if I have some extra time!

Sounds like an interesting idea, I haven't heard of this one before! In the meanwhile I'll have a look and see if we can reduce allocations manually.

On a first glance it does seem like doing this manually will require a lot of auxiliary functions, eg. ``` function Statistics.mean!(out::AbstractVector, f::PosteriorGP, x::AbstractVector) mean!(out, f.prior, x) mul!(out, cov(f.prior, x,...

A quick fix might be to store a dummy array of length `N_obs` (or two) in the GP struct to avoid having to frequently reallocate arrays of the same size.

The main computation one has to do is of the form `K_xx * K_xy` for a single input location `y`, surely one could add a simple vector or two to...