Awesome
<p align="center"> <img src="https://raw.githubusercontent.com/dfm/tinygp/main/docs/_static/zap.png" width="50"><br> <strong>tinygp</strong><br> <i>the tiniest of Gaussian Process libraries</i> <br> <br> <a href="https://github.com/dfm/tinygp/actions/workflows/tests.yml"> <img alt="GitHub Workflow Status" src="https://img.shields.io/github/actions/workflow/status/dfm/tinygp/tests.yml?branch=main"> </a> <a href="https://tinygp.readthedocs.io"> <img alt="Read the Docs" src="https://img.shields.io/readthedocs/tinygp"> </a> <a href="https://doi.org/10.5281/zenodo.6389737"> <img alt="Zenodo DOI" src="https://zenodo.org/badge/DOI/10.5281/zenodo.6389737.svg"> </a> </p>tinygp is an extremely lightweight library for building Gaussian Process (GP)
models in Python, built on top of jax. It has
a nice interface, and it's pretty fast. Thanks to
jax, tinygp supports things like GPU acceleration and automatic
differentiation.
Check out the docs for more info: tinygp.readthedocs.io