Gaussian process regression is a modern Bayesian approach to machine learning, and GPR implements some of the latest advances in this field.
Published: 22 Nov 2019
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:
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