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Random Sampling Versus Active Learning Algorithms for Machine Learning Potentials of Quantum Liquid Water
J. Chem. Theory Comput.: Joint publication RESOLV members Prof. D. Marx and Prof. J. Behler. Training accurate machine learning potentials requires electronic structure data comprehensively covering the configurational space of the system of interest. As the construction of this data is computationally demanding, many schemes for identifying the most important structures have been proposed. Here,…