The tiniest of Gaussian Process libraries.
tinygp is an extremely lightweight library for Gaussian Process (GP)
regression in Python, built on top of
is not (yet?) designed to provide all the shiniest algorithms for scalable
computations (check out celerite2 or
GPyTorch if you need something like that), but I think it
has a nice interface and it’s pretty fast. Thanks to
supports things like GPU acceleration and automatic differentiation.
How to find your way around?
👉 If you find bugs or otherwise have trouble getting
tinygp to do what you want,
head on over to the GitHub issues page.
- Why tinygp?
- Contributor Guide
- Code of Conduct