Hannes Kneiding

Δ -Machine Learning for the Prediction of Metal Complex Properties.

An adaptation of the Δ-ML strategy for quantum property prediction of transition metal complexes is presented, which consistently achieves higher accuracy in the prediction of high-fidelity targets, while demonstrating improved data efficiency and out-of-domain transferability.