79 citations · 79 across the 3 of their papers we have counts for
3 papers
Efficient hyperparameter tuning for kernel ridge regression with Bayesian optimization
Annika Stuke, Patrick Rinke, Milica Todorović
Machine learning methods usually depend on internal parameters -- so called hyperparameters -- that need to be optimized for best performance. Such optimization poses a burden on m…
Atomic structures and orbital energies of 61,489 crystal-forming organic molecules
Annika Stuke, Christian Kunkel, Dorothea Golze +5
Data science and machine learning in materials science require large datasets of technologically relevant molecules or materials. Currently, publicly available molecular datasets w…
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…