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.
(2018), PDE -Net: Learning PDE s from Data, in Proceedings of the 35th International Conference on Machine Learning, eds
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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.