JuliaGaussianProcesses/Stheno.jl

Probabilistic Programming with Gaussian processes in Julia

40
/ 100
Emerging

This tool helps researchers and data scientists analyze complex, multi-source data by modeling underlying relationships with Gaussian processes. You input various datasets with potential interdependencies, and it outputs predictions and uncertainties for unobserved data points or hidden processes. It's ideal for those working with multiple, related time series or spatial data where standard modeling approaches fall short.

344 stars. No commits in the last 6 months.

Use this if you need to build flexible probabilistic models that can handle multiple related data streams or infer hidden components from noisy observations, especially when standard Gaussian process methods are too restrictive.

Not ideal if you're looking for a simple, off-the-shelf regression or classification tool for single datasets, or if you prefer working outside the Julia programming language.

predictive-modeling time-series-analysis data-fusion uncertainty-quantification scientific-computing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

344

Forks

27

Language

Julia

License

Last pushed

Apr 01, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/JuliaGaussianProcesses/Stheno.jl"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.