MuyGPyS is toolkit for training approximate Gaussian Process (GP) models using the MuyGPs (Muyskens, Goumiri, Priest, Schneider) algorithm.
If you use MuyGPyS in a research paper, please reference our article:
@article{muygps2021,
title={MuyGPs: Scalable Gaussian Process Hyperparameter Estimation Using Local Cross-Validation},
author={Muyskens, Amanda and Priest, Benjamin W. and Goumiri, Im{\`e}ne and Schneider, Michael},
journal={arXiv preprint arXiv:2104.14581},
year={2021}
}MuyGPyS/neighbors MuyGPyS/gp MuyGPyS/optimize MuyGPyS/examples MuyGPyS/torch
examples/univariate_regression_tutorial.ipynb examples/neighborhood_illustration.ipynb examples/torch_tutorial.ipynb examples/fast_regression_tutorial.ipynb examples/anisotropic_tutorial.ipynb examples/loss_tutorial.ipynb
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