An uncertainty-sampling active learning policy plus a pseudo-streaming workflow trains neutron diffraction structure-finding models with roughly 75% less training data and about 20% shorter training time.
Unsuper- vised Machine Learning of Single Crystal X-ray Diffrac- tion Data,
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An Active Learning-Based Streaming Pipeline for Reduced Data Training of Structure Finding Models in Neutron Diffractometry
An uncertainty-sampling active learning policy plus a pseudo-streaming workflow trains neutron diffraction structure-finding models with roughly 75% less training data and about 20% shorter training time.