1 citations · 3 across the 12 of their papers we have counts for
14 papers
Almost stochastic dominance via optimal transport
Alfred Müller, Johannes Wiesel
We study parametric classes of almost stochastic dominance on general Polish spaces as order relations for probability distributions with a parameter . Larger values of…
Dependence Measures via Adapted Optimal Transport: Stability and Rates of Convergence
Jonathan Ansari, Johannes Wiesel
Recently studied dependence measures, such as Chatterjee's rank correlation, that characterize both independence and perfect functional dependence, provide a powerful framework for…
Adapted Wasserstein Barycenters of Gaussian Processes
Madhu Gunasingam, Francesco Mattesini, Johannes Wiesel +1
We study barycenters of filtered Gaussian processes in adapted Wasserstein space. The adapted Wasserstein distance refines classical optimal transport by requiring transport plans…
Convergence of the adapted empirical measure for mixing observations
Ruslan Mirmominov, Johannes Wiesel
The adapted Wasserstein distance is a modification of the classical Wasserstein metric, that provides robust and dynamically consistent comparisons of laws of stocha…
Dynamic characterization of barycentric optimal transport problems and their martingale relaxation
Ivan Guo, Severin Nilsson, Johannes Wiesel
We extend the Benamou-Brenier formula from classical optimal transport to weak optimal transport and show that the barycentric optimal transport problem studied by Gozlan and Juill…
Sample complexity for divergence regularized optimal transport with radial cost
Ruiyu Han, Johannes Wiesel
We prove a new sample complexity result for divergence regularized optimal transport. Our bound holds for probability measures on~ with exponential tail decay and for…
The fast rate of convergence of the smooth adapted Wasserstein distance
Martin Larsson, Jonghwa Park, Johannes Wiesel
Estimating a -dimensional distribution by the empirical measure of its samples is an important task in probability theory, statistics and machine learning. It is w…
A dynamic programming principle for multiperiod control problems with bicausal constraints
Ruslan Mirmominov, Johannes Wiesel
We consider multiperiod stochastic control problems with non-parametric uncertainty on the underlying probabilistic model. We derive a new metric on the space of probability measur…
Sparsity of Quadratically Regularized Optimal Transport: Bounds on concentration and bias
Johannes Wiesel, Xingyu Xu
We study the quadratically regularized optimal transport (QOT) problem for quadratic cost and compactly supported marginals and . It has been empirically observed that the o…
Bounding adapted Wasserstein metrics
Jose Blanchet, Martin Larsson, Jonghwa Park +1
The Wasserstein distance is an important instance of an optimal transport cost. Its numerous mathematical properties as well as applications to various fields such…
Max-sliced Wasserstein concentration and uniform ratio bounds of empirical measures on RKHS
Ruiyu Han, Cynthia Rush, Johannes Wiesel
Optimal transport and the Wasserstein distance have recently seen a number of applications in the fields of statistics, machine learning, data science, and the phys…
Empirical martingale projections via the adapted Wasserstein distance
Jose Blanchet, Johannes Wiesel, Erica Zhang +1
Given a collection of multidimensional pairs , we study the problem of projecting the associated suitably smoothed empirical measure onto the space of…
On the Martingale Schrödinger Bridge between Two Distributions
Marcel Nutz, Johannes Wiesel
We study a martingale Schrödinger bridge problem: given two probability distributions, find their martingale coupling with minimal relative entropy. Our main result provides Schröd…
On concentration of the empirical measure for radial transport costs
Martin Larsson, Jonghwa Park, Johannes Wiesel
Let be a probability measure on and its empirical measure with sample size . We prove a concentration inequality for the optimal transport cost between…