GaussianMarkovRandomFields.jl

Gaussian Markov Random Fields in Julia.

Introduction

Gaussian Markov Random Fields (GMRFs) are Gaussian distributions with sparse precision (inverse covariance) matrices. GaussianMarkovRandomFields.jl provides utilities for working with GMRFs in Julia. The goal is to enable flexible and efficient Bayesian inference from GMRFs, powered by sparse linear algebra.

In particular, we support the creation of GMRFs through finite element method discretizations of stochastic partial differential equations (SPDEs). This unlocks efficient GMRF-based approximations to commonly used Gaussian process priors. Furthermore, the expressive power of SPDEs allows for flexible, problem-tailored priors.

To get started with GaussianMarkovRandomFields.jl, consider going through the Tutorials.

Installation

GaussianMarkovRandomFields.jl can be installed via its GitHub repo from the Pkg REPL:

pkg> add https://github.com/timweiland/GaussianMarkovRandomFields.jl

Afterwards, you may load the package using

using GaussianMarkovRandomFields

You're good to go!