Xufan Gao

MolJam: A Multidimensional Framework for Assessing Molecular Dataset Quality and Its Impact on Machine Learning

It is demonstrated that both dataset quality and data quantity contribute to model performance and, notably, that retaining molecules with incomplete stereochemical information can outperform their removal when the resulting gain in data quantity offsets the quality penalty.