Introduces Wasserstein Tangential PCA (WT-PCA) as a variational dynamical approach to log-PCA on the Wasserstein space and derives its empirical statistical convergence rate in 2-Wasserstein distance.
Annales de l'Institut Henri Poincaré, Probabilités et Statistiques , year =
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Introduces the MCB estimator for pointwise Wasserstein barycenter quantile estimation under sparse sampling by modeling the distribution of latent unit-level quantiles via marginal CDF distributions estimated with binomial mixtures, with consistency and asymptotic normality.
citing papers explorer
-
Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence
Introduces Wasserstein Tangential PCA (WT-PCA) as a variational dynamical approach to log-PCA on the Wasserstein space and derives its empirical statistical convergence rate in 2-Wasserstein distance.