package gpr
GPR - Library and Application for Gaussian Process Regression
Install
Dune Dependency
mmottl.github.io
Readme
Changelog
LGPL-2.1-or-later WITH OCaml-LGPL-linking-exception License
Edit opam file
Versions (7)
Authors
Maintainers
Sources
gpr-1.5.1.tbz
sha256=9527297e5774378384e283e209d9b78ff1eab5c75ab54f14ad8cec8ff0634b03
sha512=1a8df8bc48edb8607c7222370642912b15debbb6ee4020056e440c80bf3e5d63bfa561fc83286fc8838bac8dbc958d0e26735a5f34b415821ae66c4a8e90f74d
doc/README.html
OCaml-GPR - Efficient Gaussian Process Regression in OCaml
This OCaml-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:

Please refer to the GPR manual for further details and to the online API documentation as programming reference.
Contact Information and Contributing
Please submit bugs reports, feature requests, contributions and similar to the GitHub issue tracker.
Up-to-date information is available at: https://mmottl.github.io/gpr
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