Published January 5, 2024
| Version v0.3.0
Software
Open
dfm/tinygp: The tiniest of Gaussian Process libraries
Creators
- 1. Center for Computational Astrophysics, Flatiron Institute, New York, NY, USA
- 2. Department of Physics and Astronomy, Bishop's University, Canada
- 3. Indian Institute of Technology Gandhinagar: Gandhinagar, Gujarat, IN
- 4. Massachusetts Institute of Technology, Probabilistic Computing Project, Cambridge, MA, USA
- 5. Department of Astronomy and the DiRAC Institute, University of Washington, Seattle, WA, USA
- 6. SRON Netherlands Institute for Space Research, Leiden, The Netherlands
- 7. Department of Physics, University of Warwick, Coventry, UK
- 8. Department of Physics and Astronomy, Aarhus University, DK
- 9. School of Public Health, Imperial College London, UK
- 10. Helmholtz-Zentrum Dresden-Rossendorf e.V.
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-v0.3.0.zip
Files
(216.4 kB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/dfm/tinygp/tree/v0.3.0 (URL)