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We solve constrained optimal transport problems in which the marginal laws are given by the laws of solutions of stochastic differential equations (SDEs). We consider SDEs with irregular coefficients, making only minimal regularity…

Probability · Mathematics 2025-10-29 Michaela Hitz , Benjamin A. Robinson

We derive explicitly the adapted $2$-Wasserstein distance between non-degenerate Gaussian distributions on $\mathbb{R}^N$ and characterize the optimal bicausal coupling(s). This leads to an adapted version of the Bures-Wasserstein distance…

Probability · Mathematics 2025-01-14 Madhu Gunasingam , Ting-Kam Leonard Wong

A number of researchers have independently introduced topologies on the set of laws of stochastic processes that extend the usual weak topology. Depending on the respective scientific background this was motivated by applications and…

Probability · Mathematics 2021-05-18 Julio Backhoff , Daniel Bartl , Mathias Beiglböck , Johannes Wiesel

We analyze the effect of small changes in the underlying probabilistic model on the value of multi-period stochastic optimization problems and optimal stopping problems. We work in finite discrete time and measure these changes with the…

Optimization and Control · Mathematics 2023-06-19 Daniel Bartl , Johannes Wiesel

Causal optimal transport and adapted Wasserstein distance have applications in different fields from optimization to mathematical finance and machine learning. The goal of this article is to provide equivalent formulations of these concepts…

Probability · Mathematics 2024-07-01 Mathias Beiglböck , Susanne Pflügl , Stefan Schrott

In this paper, we prove that the time supremum of the Wasserstein distance between the time-marginals of a uniformly elliptic multidimensional diffusion with coefficients bounded together with their derivatives up to the order $2$ in the…

Probability · Mathematics 2015-03-20 Aurélien Alfonsi , Benjamin Jourdain , Arturo Kohatsu-Higa

The adapted Wasserstein distance is a metric for quantifying distributional uncertainty and assessing the sensitivity of stochastic optimization problems on time series data. A computationally efficient alternative to it, is provided by the…

Optimization and Control · Mathematics 2025-10-10 Beatrice Acciaio , Songyan Hou , Gudmund Pammer

A number of researchers have introduced topological structures on the set of laws of stochastic processes. A unifying goal of these authors is to strengthen the usual weak topology in order to adequately capture the temporal structure of…

Probability · Mathematics 2020-09-30 Julio Backhoff-Veraguas , Daniel Bartl , Mathias Beiglböck , Manu Eder

In this paper, we introduce a variant of optimal transport adapted to the causal structure given by an underlying directed graph $G$. Different graph structures lead to different specifications of the optimal transport problem. For…

Statistics Theory · Mathematics 2024-07-08 Patrick Cheridito , Stephan Eckstein

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

Optimization and Control · Mathematics 2022-07-06 Stephan Eckstein , Marcel Nutz

The rates of strong convergence for various approximation schemes are investigated for a class of stochastic differential equations (SDEs) which involve a random time change given by an inverse subordinator. SDEs to be considered are unique…

Probability · Mathematics 2021-03-29 Sixian Jin , Kei Kobayashi

A basic and natural coupling between two probabilities on $\mathbb R^N$ is given by the Knothe-Rosenblatt coupling. It represents a multiperiod extension of the quantile coupling and is simple to calculate numerically. We consider the…

Probability · Mathematics 2023-12-29 Mathias Beiglböck , Gudmund Pammer , Alexander Posch

The Wasserstein distance $\mathcal{W}_p$ is an important instance of an optimal transport cost. Its numerous mathematical properties as well as applications to various fields such as mathematical finance and statistics have been well…

Probability · Mathematics 2025-07-09 Jose Blanchet , Martin Larsson , Jonghwa Park , Johannes Wiesel

This paper is motivated by the problem of quantitatively bounding the convergence of adaptive control methods for stochastic systems to a stationary distribution. Such bounds are useful for analyzing statistics of trajectories and…

Optimization and Control · Mathematics 2021-10-19 Tyler Lekang , Andrew Lamperski

We present a pair of adjoint optimal control problems characterizing a class of time-symmetric stochastic processes defined on random time intervals. The associated PDEs are of free-boundary type. The particularity of our approach is that…

Probability · Mathematics 2020-07-07 Ana Bela Cruzeiro , Carlos Oliveira , Jean-Claude Zambrini

Adapted or causal transport theory aims to extend classical optimal transport from probability measures to stochastic processes. On a technical level, the novelty is to restrict to couplings which are bicausal, i.e. satisfy a property which…

Probability · Mathematics 2025-10-21 Mathias Beiglböck , Gudmund Pammer , Stefan Schrott

We obtain the first probabilistic proof of continuous differentiability of time-dependent optimal boundaries in optimal stopping problems. The underlying stochastic dynamics is a one-dimensional, time-inhomogeneous diffusion. The gain…

Probability · Mathematics 2024-05-28 Tiziano De Angelis , Damien Lamberton

This work investigates several aspects related to quantitative stability in optimal transport, as well as uniqueness of the dual transport problem. Our main contributions are as follows. Chapter 1: Observations regarding the quantitative…

Functional Analysis · Mathematics 2025-10-22 William Ford

We are interested in the following two $\mathbb{R}^d$-valued stochastic differential equations (SDEs): \begin{gather*} d X_t=b(X_t)\,d t + \sigma\,d L_t, \quad X_0=x, %\label{BM-SDE} d Y_t=b(Y_t)\,d t + \sigma\,d B_t, \quad Y_0=y,…

Probability · Mathematics 2024-03-06 Changsong Deng , Rene L. Schilling , Lihu Xu

We study the discretization of generalized Wasserstein distances with nonlinear mobilities on the real line via suitable discrete metrics on the cone of N ordered particles, a setting which naturally appears in the framework of…

Analysis of PDEs · Mathematics 2022-09-01 Simone Di Marino , Lorenzo Portinale , Emanuela Radici
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