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.