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We investigate a stochastic program with expected value constraints, addressing the problem in a general context through Distributionally Robust Optimization (DRO) approach using Wasserstein distances, where the ambiguity set depends on the…

Optimization and Control · Mathematics 2023-04-18 Diego Fonseca , Mauricio Junca

We prove the existence of weak solutions to a system of two diffusion equations that are coupled by a pointwise volume constraint. The time evolution is given by gradient dynamics for a free energy functional. Our primary example is a model…

Analysis of PDEs · Mathematics 2020-03-18 Clément Cancès , Daniel Matthes

This paper studies minimax optimization problems defined over infinite-dimensional function classes of overparameterized two-layer neural networks. In particular, we consider the minimax optimization problem stemming from estimating linear…

Machine Learning · Computer Science 2024-10-25 Yuchen Zhu , Yufeng Zhang , Zhaoran Wang , Zhuoran Yang , Xiaohong Chen

We analyze some parabolic PDEs with different drift terms which are gradient flows in the Wasserstein space and consider the corresponding discrete-in-time JKO scheme. We prove with optimal transport techniques how to control the L p and L…

Analysis of PDEs · Mathematics 2019-11-26 Simone Di Marino , Filippo Santambrogio

We develop a new computational framework to solve the partial differential equations (PDEs) governing the flow of the joint probability density functions (PDFs) in continuous-time stochastic nonlinear systems. The need for computing the…

Optimization and Control · Mathematics 2019-08-08 Kenneth F. Caluya , Abhishek Halder

Convexity properties of the entropy along displacement interpolations are crucial in the Lott-Sturm-Villani theory of lower bounded curvature of geodesic measure spaces. As discrete spaces fail to be geodesic, an alternate analogous theory…

Probability · Mathematics 2022-09-05 Christian Léonard

We consider optimization of the average entropy production in inhomogeneous temperature environments within the framework of stochastic thermodynamics. For systems modeled by Langevin equations (e.g. a colloidal particle in a heat bath) it…

Statistical Mechanics · Physics 2013-03-14 Stefano Bo , Erik Aurell , Ralf Eichhorn , Antonio Celani

We propose a variational finite volume scheme to approximate the solutions to Wasserstein gradient flows. The time discretization is based on an implicit linearization of the Wasserstein distance expressed thanks to Benamou-Brenier formula,…

Numerical Analysis · Mathematics 2019-07-22 Clément Cancès , Thomas O. Gallouët , Gabriele Todeschi

We study a stochastic optimal control problem for jump-diffusion systems whose drift coefficient is piecewise Lipschitz continuous and exhibits threshold-induced discontinuities. Such dynamics naturally arise in applications with…

Optimization and Control · Mathematics 2026-05-08 Antoine-Marie Bogso , Edward Fuituh Kameh , Olivier Menoukeu-Pamen , Felix Shu

We deal with the task of sampling from an unnormalized Boltzmann density $\rho_D$ by learning a Boltzmann curve given by energies $f_t$ starting in a simple density $\rho_Z$. First, we examine conditions under which Fisher-Rao flows are…

Machine Learning · Computer Science 2024-10-07 Jannis Chemseddine , Christian Wald , Richard Duong , Gabriele Steidl

One of the most enigmatic science question concerning inertial particle transport by a turbulent boundary layer flow is the value of the turbulent Schmidt number as the ratio of particle diffusivity and turbulent eddy viscosity. Using…

Fluid Dynamics · Physics 2021-12-14 Julien Chauchat , David Hurther , Thibaud Revil-Baudard , Zhen Cheng , Tian-Jian Hsu

This paper studies time-inhomogeneous nonequilibrium diffusion processes, including both Brownian dynamics and Langevin dynamics. We derive upper bounds of the relative entropy production of the time-inhomogeneous process with respect to…

Probability · Mathematics 2021-04-20 Wei Zhang

In this article, we investigate some of the fine properties of the value function associated to an optimal control problem in the Wasserstein space of probability measures. Building on new interpolation and linearisation formulas for…

Optimization and Control · Mathematics 2021-11-29 Benoît Bonnet , Hélène Frankowska

Wasserstein barycenters provide a principled approach for aggregating probability measures, while preserving the geometry of their ambient space. Existing discrete methods are not scalable as they assume access to the complete set of…

Machine Learning · Statistics 2026-03-10 Eduardo Fernandes Montesuma , Yassir Bendou , Mike Gartrell

We investigate the kinetic Schr\"odinger problem, obtained considering Langevin dynamics instead of Brownian motion in Schr\"odinger's thought experiment. Under a quasilinearity assumption we establish exponential entropic turnpike…

Probability · Mathematics 2022-09-09 Alberto Chiarini , Giovanni Conforti , Giacomo Greco , Zhenjie Ren

We observe the emergence of a distinct, elasticity-driven flow state in a yield-stress fluid in the absence of inertia. Numerical simulations show that this elasto-plastic turbulent state is characterized by a broad spectrum of fluctuations…

Multimarginal optimal transport (MOT) has emerged as a useful framework for many applied problems. However, compared to the well-studied classical two-marginal optimal transport theory, analysis of MOT is far more challenging and remains…

Statistics Theory · Mathematics 2026-01-01 Pengtao Li , Xiaohui Chen

The Wasserstein barycenter extends the Euclidean mean to the space of probability measures by minimizing the weighted sum of squared 2-Wasserstein distances. We develop a free-support algorithm for computing Wasserstein barycenters that…

Machine Learning · Statistics 2025-09-17 Kisung You

We derive a Maximum Principle for optimal control problems with constraints given by the coupling of a system of ODEs and a PDE of Vlasov-type. Such problems arise naturally as ${\Gamma}$-limits of optimal control problems subject to ODE…

Optimization and Control · Mathematics 2015-04-10 Mattia Bongini , Massimo Fornasier , Francesco Rossi , Francesco Solombrino

The nature of particle and entropy flow between two superfluids is often understood in terms of reversible flow carried by an entropy-free, macroscopic wavefunction. While this wavefunction is responsible for many intriguing properties of…

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