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GPR
Library for doing GPR (Gaussian Process Regression) in OCaml. Comes with a command line application.
About GPR
GPR is an OCaml library for Gaussian process regression. It implements approximation algorithms such as SPGP for scalable regression with arbitrary covariance functions, and comes with a command line example application.
Key features
- Performs Gaussian process regression in OCaml
- Supports arbitrary covariance functions
- Implements SPGP approximation for scalable regression
- Includes command line example application
Best for: OCaml developers who need Gaussian process regression with arbitrary covariance functions.
Good for
- Supports arbitrary covariance functions
- Uses approximation algorithms for scalable regression
- Includes an example command line application
GPR at a glance
- Website
- mmottl.github.io/gpr
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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GPR FAQ
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Submit bug reports, feature requests, and contributions to the GitHub issue tracker.
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