Probst, Daniel2023-03-272023-03-272023-03-272023-03-0910.1038/s41570-023-00480-3https://infoscience.epfl.ch/handle/20.500.14299/196411WOS:000945756200001Owing to the diminishing returns of deep learning and the focus on model accuracy, machine learning for chemistry might become an endeavour exclusive to well-funded institutions and industry. Extending the focus to model efficiency and interpretability will make machine learning for chemistry more inclusive and drive methodological progress.Chemistry, MultidisciplinaryChemistrytext::journal::journal article::review article