Panaretos, V. M. & Zemel, Y. (2020)
An Invitation to Statistics in Wasserstein Spaces
Springer Briefs in Probability & Mathematical Statistics.
Heinemann, F., Munk, A., & Zemel, Y. (2021+)
Randomised Wasserstein barycenter computation: Resampling with statistical guarantees.
SIAM Journal of Mathematics of Data Science, in press. The accompanying R package WSGeometry is available from CRAN
Klatt, M., Munk, A., & Zemel, Y. (2020+)
Limit laws for empirical optimal solutions in stochastic linear programs.
Submitted
Galasso, B., Zemel, Y. & de Carvalho, M. (2018+)
Bayesian semiparametric modelling of phase-varying point processes.
Electronic Journal of Statistics (in press). The accompanying R package Rmpp is available from GitHub
Zemel, Y. & Panaretos, V. M. (2019)
Fréchet Means and Procrustes Analysis in Wasserstein Space.
Bernoulli 25(2):932-976
Masarotto, V., Panaretos, V. M. & Zemel, Y. (2019)
Procrustes metrics on covariance operators and optimal transportation of Gaussian processes.
Invited paper, Special Issue on Manifold Statistics, Sankhya A 81(1):172-213
Panaretos, V. M. & Zemel, Y. (2019)
Statistical Aspects of Wasserstein Distances.
Annual Review of Statistics and its Applications 6:405-431
Sommerfeld, M., Schrieber, J., Zemel, Y. & Munk, A. (2019)
Optimal Transport: Fast probabilistic Approximation with Exact Solvers.
Journal of Machine Learning Research 20(105):1-23
Henshaw, J. M. & Zemel, Y. (2017)
A unified measure of linear and nonlinear selection on quantitative traits.
Methods in Ecology and Evolution 8(5):604-614
This paper won the Robert May Prize, awarded to the first author by convention.
R code available on GitHub
Panaretos, V. M. & Zemel, Y. (2016)
Amplitude and phase variation of point processes.
The Annals of Statistics 44(2):771-812
The accompanying R package Rmpp is available from GitHub