SENECA uses a novel self-consistent missing mass calculation to improve discrete entropy estimates in small-sample regimes and outperforms alternatives in numerical tests.
Nonparametric Estimation of the Number of Classes in a Population.Scandinavian Journal of Statistics, pages 265–270
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CONSIGN applies conformal prediction to segmentation by incorporating spatial structure through decomposition, producing tighter and more interpretable uncertainty estimates with error guarantees.
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SENECA: Small-Sample Discrete Entropy Estimation via Self-Consistent Missing Mass
SENECA uses a novel self-consistent missing mass calculation to improve discrete entropy estimates in small-sample regimes and outperforms alternatives in numerical tests.
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CONSIGN: Conformal Segmentation Informed by Spatial Groupings via Decomposition
CONSIGN applies conformal prediction to segmentation by incorporating spatial structure through decomposition, producing tighter and more interpretable uncertainty estimates with error guarantees.