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Zhenhua Lin, Dehan Kong and Linbo Wang Journal of the Royal Statistical Society Series B: Statistical Methodology 85(2) 378 (2023) https://doi.org/10.1093/jrsssb/qkad008
Simple approximative algorithms for free-support Wasserstein barycenters
Hellinger–Kantorovich barycenter between Dirac measures
Mauro Bonafini, Olga Minevich and Bernhard Schmitzer ESAIM: Control, Optimisation and Calculus of Variations 29 19 (2023) https://doi.org/10.1051/cocv/2022088
Randomized Wasserstein Barycenter Computation: Resampling with Statistical Guarantees
Florian Heinemann, Axel Munk and Yoav Zemel SIAM Journal on Mathematics of Data Science 4(1) 229 (2022) https://doi.org/10.1137/20M1385263
Bayesian learning with Wasserstein barycenters
Julio Backhoff-Veraguas, Joaquin Fontbona, Gonzalo Rios and Felipe Tobar ESAIM: Probability and Statistics 26 436 (2022) https://doi.org/10.1051/ps/2022015
Detecting the Spatial Mismatch of Water Resources and Grain Planting Pattern Changes in China Based on Satellite Data
Ensemble Riemannian data assimilation: towards large-scale dynamical systems
Sagar K. Tamang, Ardeshir Ebtehaj, Peter Jan van Leeuwen, Gilad Lerman and Efi Foufoula-Georgiou Nonlinear Processes in Geophysics 29(1) 77 (2022) https://doi.org/10.5194/npg-29-77-2022
Global Sensitivity Analysis and Wasserstein Spaces
Jean-Claude Fort, Thierry Klein and Agnès Lagnoux SIAM/ASA Journal on Uncertainty Quantification 9(2) 880 (2021) https://doi.org/10.1137/20M1354957
Distributionally robust portfolio maximization and marginal utility pricing in one period financial markets
Entropic-Wasserstein Barycenters: PDE Characterization, Regularity, and CLT
Guillaume Carlier, Katharina Eichinger and Alexey Kroshnin SIAM Journal on Mathematical Analysis 53(5) 5880 (2021) https://doi.org/10.1137/20M1387262
Barycenters for the Hellinger--Kantorovich Distance Over $\mathbb{R}^d$
Gero Friesecke, Daniel Matthes and Bernhard Schmitzer SIAM Journal on Mathematical Analysis 53(1) 62 (2021) https://doi.org/10.1137/20M1315555
An Invitation to Statistics in Wasserstein Space
Victor M. Panaretos and Yoav Zemel SpringerBriefs in Probability and Mathematical Statistics, An Invitation to Statistics in Wasserstein Space 59 (2020) https://doi.org/10.1007/978-3-030-38438-8_3
Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding
François Bachoc, Alexandra Suvorikova, David Ginsbourger, Jean-Michel Loubes and Vladimir Spokoiny Electronic Journal of Statistics 14(2) (2020) https://doi.org/10.1214/20-EJS1725
An Invitation to Statistics in Wasserstein Space
Victor M. Panaretos and Yoav Zemel SpringerBriefs in Probability and Mathematical Statistics, An Invitation to Statistics in Wasserstein Space 75 (2020) https://doi.org/10.1007/978-3-030-38438-8_4
Central limit theorem and bootstrap procedure for Wasserstein’s variations with an application to structural relationships between distributions
Eustasio del Barrio, Paula Gordaliza, Hélène Lescornel and Jean-Michel Loubes Journal of Multivariate Analysis 169 341 (2019) https://doi.org/10.1016/j.jmva.2018.09.014