Composite Silhouette combines micro- and macro-averaged Silhouette scores from multiple subsampled clusterings via adaptive weighting to recover the ground-truth number of clusters more accurately than either averaging method alone.
Communica- tions in Statistics-theory and Methods3(1), 1–27 (1974)
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A mixture-of-experts transformer foundation model pretrained on diverse SEM images enables generalization across materials and outperforms SOTA on unsupervised defocus-to-focus restoration.
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Composite Silhouette: A Subsampling-based Aggregation Strategy
Composite Silhouette combines micro- and macro-averaged Silhouette scores from multiple subsampled clusterings via adaptive weighting to recover the ground-truth number of clusters more accurately than either averaging method alone.
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A Mixture of Experts Foundation Model for Scanning Electron Microscopy Image Analysis
A mixture-of-experts transformer foundation model pretrained on diverse SEM images enables generalization across materials and outperforms SOTA on unsupervised defocus-to-focus restoration.