While in other fields this problem is alleviated through data augmentation, i.e. an artificial increase of the number of observations of the training set to help the model generalize, this regularization technique is not yet commonly used in CADD. Some studies have considered different variants of the SMILES of each molecule as a way of data augmentation, but despite its proven benefits, its use is not widespread yet. This is partly due to the lack of consensus in the input representations, where alternatives to SMILES are often used.