Before revision:  Our key findings include: Physicochemical descriptors and deep learning-based graph representations are significantly better than traditional fingerprints to characterize molecular featuresDataset size is directly correlated to performance of prediction : single-task deep learning models only outperform shallow learners if there is enough data.
After revision:  As a result of these comprehensive experiments, we have found that physicochemical descriptors and deep learning-based graph representations are significantly better than traditional fingerprints to characterize molecular featuresDataset size is directly correlated to performance of prediction : single-task deep learning models only outperform shallow learners if there is enough data.