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Published September 30, 2023 | Version v0.2.4rc2
Software Open

dfm/tinygp: The tiniest of Gaussian Process libraries

Authors/Creators

  • 1. Center for Computational Astrophysics, Flatiron Institute, New York, NY, USA
  • 2. Indian Institute of Technology Gandhinagar: Gandhinagar, Gujarat, IN
  • 3. Massachusetts Institute of Technology, Probabilistic Computing Project, Cambridge, MA, USA
  • 4. Department of Physics, University of Warwick, Coventry, UK
  • 5. School of Public Health, Imperial College London, UK
  • 6. Helmholtz-Zentrum Dresden-Rossendorf e.V.
  • 7. Department of Physics and Astronomy, Aarhus University, DK
  • 8. Department of Astronomy and the DiRAC Institute, University of Washington, Seattle, WA, USA

Description

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: https://tinygp.readthedocs.io

Files

dfm/tinygp-v0.2.4rc2.zip

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Additional details

Related works

Is supplement to
https://github.com/dfm/tinygp/tree/v0.2.4rc2 (URL)