Unsupervised machine learning with multivariate Gaussian mixture model.
Open source
24 alternativesGaussian Processes
GaussianProcesses.jl is a Julia package for working with Gaussian processes.
About Gaussian Processes
GaussianProcesses.jl is a Julia package for fitting Gaussian process models, a nonparametric Bayesian method that places a prior over functions. The main GP function fits a model from training points, a mean function, a kernel, and optionally a likelihood; exact fits apply when observations are Gaussian distributed about the latent function, while non-Gaussian data are handled by Monte Carlo sampling from the posterior. The package requires Julia version 0.7 or above and is installed with Pkg.add("GaussianProcesses").
Key features
- Fits exact Gaussian process models for Gaussian-distributed observations
- Supports Monte Carlo sampling from the posterior for non-Gaussian data
- Estimates parameters by maximizing log-likelihood with optimize!
- Offers Hamiltonian Monte Carlo sampling through the mcmc function
- Provides an elliptical slice sampler for Gaussian likelihood data
- Variational approximation (vi) for fast, approximate inference on Poisson data
Best for: Researchers and statisticians working in Julia who need nonparametric Bayesian modelling of data with Gaussian processes.
Good for
- Combines model fitting, parameter estimation and posterior sampling in one package
- Provides several inference routes: log-likelihood optimization, Hamiltonian Monte Carlo, elliptical slice sampling and a variational approximation
- Documentation is available in the Julia REPL help mode, with notebooks showing example usage
Watch out for
- Requires Julia version 0.7 or above
- The elliptical slice sampler applies only when the data exhibits a Gaussian likelihood
- The variational approximation covers Poisson data and is approximate rather than exact
Gaussian Processes at a glance
- Category
- AI & Machine Learning › Models & ML Research
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Gaussian Processes FAQ
What Julia version does GaussianProcesses.jl require?
It requires Julia version 0.7 or above.
How do you install the package?
Inside a Julia session, run using Pkg followed by Pkg.add("GaussianProcesses").
How should the package be cited?
Reference the paper by Fairbrother, Nemeth, Rischard, Brea and Pinder, "GaussianProcesses.jl: A Nonparametric Bayes Package for the Julia Language," Journal of Statistical Software, volume 102, pages 1-36, 2022.
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