Active learning framework that combines D-optimality with maximin space-filling via Gaussian process surrogates to recover governing differential equations with fewer experiments than standard designs.
(1996), Regression Shrinkage and Selection via the Lasso, Journal of the Royal Statistical Society, 58, 267--288
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Gaussian Process Assisted Active Learning of Physical Laws
Active learning framework that combines D-optimality with maximin space-filling via Gaussian process surrogates to recover governing differential equations with fewer experiments than standard designs.