package gpr

  1. Overview
  2. Docs
GPR - Library and Application for Gaussian Process Regression

Install

Dune Dependency

Authors

Maintainers

Sources

gpr-1.5.1.tbz
sha256=9527297e5774378384e283e209d9b78ff1eab5c75ab54f14ad8cec8ff0634b03
sha512=1a8df8bc48edb8607c7222370642912b15debbb6ee4020056e440c80bf3e5d63bfa561fc83286fc8838bac8dbc958d0e26735a5f34b415821ae66c4a8e90f74d

Description

Gaussian process regression is a modern Bayesian approach to machine learning, and GPR implements some of the latest advances in this field.

Published: 25 Nov 2024

README

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

Dependencies (7)

  1. gsl >= "1.24.0"
  2. lacaml >= "11.0.0"
  3. core_unix >= "v0.13"
  4. core >= "v0.13"
  5. base-threads
  6. ocaml >= "4.08"
  7. dune >= "2.7"

Dev Dependencies (1)

  1. odoc with-doc

Used by

None

Conflicts

None

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