Using Deep Graph Neural Networks Improves Physics-Based Hydration Free Energy Predictions Even for Molecules Outside of the Training Set Distribution.

This lack of a clear trend is likely due to noise as a result of the small data set, making it is difficult to make stronger conclusions on the impact of physics model accuracy on predictions for molecules with out-of-distribution molecular scaffolds.

also in 19,460 other papers