llnl/MuyGPyS
A fast, pure python implementation of the MuyGPs Gaussian process realization and training algorithm.
This project helps data scientists and machine learning engineers analyze very large datasets, often with millions or billions of observations, by using Gaussian Process models. You provide a dataset with features and target values, and it outputs predictions and uncertainty estimates quickly, even on standard laptops or distributed systems.
No commits in the last 6 months. Available on PyPI.
Use this if you need accurate predictions and quantified uncertainty on datasets too large for traditional Gaussian Process methods.
Not ideal if your datasets are small to moderately sized, where a standard Gaussian Process library might be simpler to implement.
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Language
Python
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Last pushed
Sep 26, 2025
Commits (30d)
0
Dependencies
4
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