Critical examination of active learning workflows for data-efficient machine learning in materials science, indicating its significance in autonomous discovery.
Active learning (AL) is an increasingly important approach for data-efficient machine learning (ML) in materials science. It is widely used, from building training datasets to guiding autonomous materials discovery platforms....
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Nair et al. (2026) studied this question.
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