922 citations · 3.5k across the 16 of their papers we have counts for
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Chemical diversity in molecular orbital energy predictions with kernel ridge regression
Annika Stuke, Milica Todorović, Matthias Rupp +4
Instant machine learning predictions of molecular properties are desirable for materials design, but the predictive power of the methodology is mainly tested on well-known benchmar…
Machine-learned multi-system surrogate models for materials prediction
Chandramouli Nyshadham, Matthias Rupp, Brayden Bekker +6
Surrogate machine-learning models are transforming computational materials science by predicting properties of materials with the accuracy of ab initio methods at a fraction of the…
Guest Editorial: Special Topic on Data-enabled Theoretical Chemistry
Matthias Rupp, O. Anatole von Lilienfeld, Kieron Burke
A survey of the contributions to the Special Topic on Data-enabled Theoretical Chemistry is given, including a glossary of relevant machine learning terms.