https://github.com/mmottl/gpr

Library for doing GPR (Gaussian Process Regression) in OCaml. Comes with a command line application.
https://github.com/mmottl/gpr

gaussian-process-regression gaussian-processes machine-learning ocaml regression

Last synced: about 1 year ago
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Library for doing GPR (Gaussian Process Regression) in OCaml. Comes with a command line application.

• Host: GitHub
• URL: https://github.com/mmottl/gpr
• Owner: mmottl
• License: other
• Created: 2014-07-03T21:28:32.000Z (almost 12 years ago)
• Default Branch: master
• Last Pushed: 2025-01-19T17:16:54.000Z (over 1 year ago)
• Last Synced: 2025-04-01T22:03:27.727Z (about 1 year ago)
• Topics: gaussian-process-regression, gaussian-processes, machine-learning, ocaml, regression
• Language: OCaml
• Size: 2.89 MB
• Stars: 47
• Watchers: 6
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE.md

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README

          
# OCaml-GPR - Efficient Gaussian Process Regression in OCaml

This [OCaml](http://www.ocaml.org)-library, which also comes with an elaborate

example application, implements some of the newest approximation algorithms

(e.g. _SPGP_) for scalable Gaussian process regression for arbitrary covariance

functions. Here is an example graph showing the fit of such a sparse Gaussian

process to a nonlinear function:

![Sparse Gaussian Process](http://mmottl.github.io/gpr/fit.png "Sparse Gaussian Process")

Please refer to the [GPR manual](http://mmottl.github.io/gpr/gpr_manual.pdf)

for further details and to the [online API

documentation](http://mmottl.github.io/gpr/api/gpr) as programming reference.

## Contact Information and Contributing

Please submit bugs reports, feature requests, and contributions to the

[GitHub issue tracker](https://github.com/mmottl/gpr/issues).

Up-to-date information is available at: