Fig. 1. Overall idea behind the DelFTa software package. Δ-learning models were trained to predict the correction (Δ) between observables computed with a lower-cost semiempirical baseline method (GFN2-xTB) and the corresponding DFT-level reference method (ωB97X-D/def2-SVP). Visualization inspired by ref. 34.