Context-aware neural network conditions defect classification on experimental metadata, raising simulated accuracy above 98% and cutting posterior entropy by 94% across 96 doped 2D materials.
Obtaining well calibrated probabilities using bayesian binning
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Context-Aware Deep Learning for Defect Classification in Atomic-Resolution STEM
Context-aware neural network conditions defect classification on experimental metadata, raising simulated accuracy above 98% and cutting posterior entropy by 94% across 96 doped 2D materials.