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Found 3 papers, 2 papers with code
Gaussian Processes on Hypergraphs
We derive a Matern Gaussian process (GP) on the vertices of a hypergraph.
Stein Variational Gaussian Processes
We show how to use Stein variational gradient descent (SVGD) to carry out inference in Gaussian process (GP) models with non-Gaussian likelihoods and large data volumes.
GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language
Gaussian processes are a class of flexible nonparametric Bayesian tools that are widely used across the sciences, and in industry, to model complex data sources.
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