Data augmented bootstrap constructs confidence intervals via approximately invariant transformations, recovering classical bootstrap, conformal prediction, wild bootstrap, and SymmPI as special cases with interpolated finite-sample to asymptotic coverage guarantees.
arXiv preprint arXiv:2409.05202 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
SNR-ST-Mix is a geometry- and expression-aware mixup augmentation that constrains interpolation to k-nearest spatial neighbors and weights by transcriptomic similarity for spatial transcriptomics imputation.
citing papers explorer
-
Data augmented bootstrap: Unifying confidence interval construction by approximate invariance
Data augmented bootstrap constructs confidence intervals via approximately invariant transformations, recovering classical bootstrap, conformal prediction, wild bootstrap, and SymmPI as special cases with interpolated finite-sample to asymptotic coverage guarantees.