One compound in the test set (mobley 4587267, (2R,3R,4R,5R)-hexane-1,2,3,4,5,6-hexol, referred to as mannitol from hereon) stands out with a free energy of hydration significantly more negative than other compounds in the test set (∼ -24 kcal•mol -1 ). This compound has a large associated ∆G of f set value of ∼-5 kcal•mol -1 (figures 1A and 1B, resp.). SVM and MLR models appear to correct this outlier better than RF and DNN models do, and it is likely that this outlier correction skews the statistical performances of the four models to a degree (see table for model performances excluding the outlier); indeed, when plugging in the correction terms (figure ), FEP/ML FE predictions for mannitol appear to be close to experimental hydration free energy measures, especially for SVM and MLR models. The top-performing FEP/ML model (SVM; MolPropsAPFP, Figure ) outperformed standalone FEP in Pearson r, MUE and RMSE statistics and had higher ranking statistics (Spearman ρ and Kendall τ ) than standalone FEP (see table ). The top-performing FEP/ML DNN model achieves similar accuracy, but introduces significant uncertainties compared to FEP (Figure ). This reflects the larger uncertainties of the DNN-derived offset values in comparison with other ML protocols (see Figure ). Even when offset predic- .