866 citations · 988 across the 9 of their papers we have counts for
11 papers
Gaussian Optimal Transport Beyond Brenier's Theorem
Ho Yun, Yoav Zemel
We explore the geometry of the Bures-Wasserstein space for potentially degenerate Gaussian measures on a separable Hilbert space. In this general setting, the optimal transport map…
Non-injectivity of Bures--Wasserstein barycentres in infinite dimensions
Yoav Zemel
We construct a counterexample to the injectivity conjecture of Masarotto et al (2018). Namely, we construct a class of examples of injective covariance operators on an infinite-dim…
Transportation-Based Functional ANOVA and PCA for Covariance Operators
Valentina Masarotto, Victor M. Panaretos, Yoav Zemel
We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second…
Randomised Wasserstein Barycenter Computation: Resampling with Statistical Guarantees
Florian Heinemann, Axel Munk, Yoav Zemel
We propose a hybrid resampling method to approximate finitely supported Wasserstein barycenters on large-scale datasets, which can be combined with any exact solver. Nonasymptotic…
Limit Laws for Empirical Optimal Solutions in Stochastic Linear Programs
Marcel Klatt, Axel Munk, Yoav Zemel
We consider a general linear program in standard form whose right-hand side constraint vector is subject to random perturbations. This defines a stochastic linear program for which…
Bayesian semiparametric modelling of phase-varying point processes
Bastian Galasso, Yoav Zemel, Miguel de Carvalho
We propose a Bayesian semiparametric approach for registration of multiple point processes. Our approach entails modelling the mean measures of the phase-varying point processes wi…
Statistical Aspects of Wasserstein Distances
Victor M. Panaretos, Yoav Zemel
Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to…
Optimal Transport: Fast Probabilistic Approximation with Exact Solvers
Max Sommerfeld, Jörn Schrieber, Yoav Zemel +1
We propose a simple subsampling scheme for fast randomized approximate computation of optimal transport distances. This scheme operates on a random subset of the full data and can…
Procrustes Metrics on Covariance Operators and Optimal Transportation of Gaussian Processes
Valentina Masarotto, Victor M. Panaretos, Yoav Zemel
Covariance operators are fundamental in functional data analysis, providing the canonical means to analyse functional variation via the celebrated Karhunen--Loève expansion. These…
Fréchet Means and Procrustes Analysis in Wasserstein Space
Yoav Zemel, Victor M. Panaretos
We consider two statistical problems at the intersection of functional and non-Euclidean data analysis: the determination of a Fréchet mean in the Wasserstein space of multivariate…
Amplitude and phase variation of point processes
Victor M. Panaretos, Yoav Zemel
We develop a canonical framework for the study of the problem of registration of multiple point processes subjected to warping, known as the problem of separation of amplitude and…