A Gaussian process interpolation pipeline with a coverage-based hyperparameter tune is proposed for sparse hadron spectroscopy data; validation is largely in-sample.
Pedregosa et al., Scikit-learn: Machine learning in Py- thon, Journal of Machine Learning Research 12, 2825 (2011)
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Data-driven Approach for Interpolation of Sparse Data
A Gaussian process interpolation pipeline with a coverage-based hyperparameter tune is proposed for sparse hadron spectroscopy data; validation is largely in-sample.