ASCL Code Record
[ascl:1709.008]
celerite: Scalable 1D Gaussian Processes in C++, Python, and Julia
celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.
celerite has been superceded by celerite2 (ascl:2310.001).
- Code site:
- https://github.com/dfm/celerite https://github.com/ericagol/celerite.jl https://celerite.readthedocs.io/en/stable/
- Described in:
- https://ui.adsabs.harvard.edu/abs/2017AJ....154..220F
- Bibcode:
- 2017ascl.soft09008F
Preferred citation method:
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