Publication

Aiming beyond slight increases in accuracy

Daniel Probst
2023
Journal paper
Abstract

Owing 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.

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