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GP Sampling

Update: This functionality is now available in BoTorch, see here. It is recommended to use the BoTorch version since it will be better maintained going forward.

A minimal implementation of decoupled samplers from "Efficiently Sampling Functions from Gaussian Process Posteriors" (https://arxiv.org/abs/2002.09309) on BoTorch / GPyTorch.

Original implementation by the author (based on GPflow) is found at https://github.com/j-wilson/GPflowSampling .

Supports decoupled sampling from BoTorch SingleTaskGP models. It is set to work with the default Matern kernel (ScaleKernel(MaternKernel(...))), and also supports the Squared Exponential kernel (ScaleKernel(RBFKernel(...))).

See notebooks/ for examples.

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