Research Interests
- Nonparametric statistics, and in particular optimal transport
- Point processes
- Gaussian processes
Dr Yoav Zemel
Dr Yoav Zemel is a College Research Associate at Magdalene College.
Dr Yoav Zemel obtained a B.Sc. from the Hebrew University of Jerusalem and M.Sc. and Ph.D. from the Ecole polytechnique fédérale de Lausanne. He then moved to the University of Göttingen as a Swiss National Science Foundation postdoctoral fellow. Yoav joined the Statistical Laboratory at Cambridge in 2019 to work with Richard Samworth, and Magdalene in 2020.
Qualifications
B.Sc. Mathematics and Economics, Hebrew University of Jerusalem
M.Sc. Applied Mathematics, orientated in Statistics and Financial Mathematics, École polytechnique fédérale de Lausanne
PhD, École polytechnique fédérale de Lausanne
Selected Publications
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