Machine Learning Reactivity in the Chemical Space Surrounding Vaska's Complex

27 November 2019, Version 1


Machine learning models, including neural networks, Bayesian optimization, gradient boosting and Gaussian processes, were trained with DFT data for the accurate, affordable and explainable prediction of hydrogen activation barriers in the chemical space surrounding Vaska's complex.


Supplementary materials

Learning Barriers SI ChRx
Vaskas Space Data


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