Reward-driven hyperparameter selection guided by domain-wall straightness and continuity steers unsupervised clustering and variational autoencoders toward physically meaningful phase and ferroic-variant maps in Sm-doped BiFeO3.
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Reward driven workflows for unsupervised explainable analysis of phases and ferroic variants from atomically resolved imaging data
Reward-driven hyperparameter selection guided by domain-wall straightness and continuity steers unsupervised clustering and variational autoencoders toward physically meaningful phase and ferroic-variant maps in Sm-doped BiFeO3.