Titlebook: Machine Learning Meets Quantum Physics; Kristof T. Schütt,Stefan Chmiela,Klaus-Robert Müll Book 2020 The Editor(s) (if applicable) and The

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Building Nonparametric ,-Body Force Fields Using Gaussian Process Regressionich this problem can be tackled, based on the Bayesian construction of nonparametric force fields of a given order using Gaussian process (GP) priors. The formalism of GP regression is first reviewed, particularly in relation to its application in learning local atomic energies and forces. For accur

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Quantum Machine Learning with Response Operators in Chemical Compound Spaceel ridge regression (KRR). A carefully constructed representation can lower the prediction error for out-of-sample data by several orders of magnitude with the same training data. This is a particularly desirable effect in data scarce scenarios, such as they are common in first principles based chem