tinygp

The tiniest of Gaussian Process libraries.

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 (see Benchmarks). Thanks to jax, tinygp supports things like GPU acceleration and automatic differentiation.

How to find your way around?

🖥 A good place to get started is with the Installation Guide and then the Tutorials. You might also be interested in the Why tinygp? page.

📖 For all the details, check out the User Guide, including the full API documentation.

💡 If you’re running into getting tinygp to do what you want, first check out the Troubleshooting page, for some general tips and tricks.

🐛 If Troubleshooting doesn’t solve your problems, or if you find bugs, check out the Contributor Guide and then head on over to the GitHub issues page.

👈 Check out the sidebar to find the full table of contents.

Table of contents

• User Guide
  • Why tinygp?
  • Installation Guide
  • Troubleshooting
  • Benchmarks
  • Release Notes
• Tutorials
  • Introductory Topics
  • Advanced Topics
• Contributor Guide
  • How to report a bug
  • How to request a feature
  • How to test the project
  • How to submit changes
  • Making a new release
• Public API
  • Primary Interface
  • Subpackages
• GitHub Repository

Authors & license

Copyright 2021, 2022, 2023 Simons Foundation, Inc.

Built by Dan Foreman-Mackey and contributors (see the contribution graph for the most up-to-date list). Licensed under the MIT license (see LICENSE).