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Let $M$ be a $d$-dimensional connected compact Riemannian manifold with boundary $\partial M$, let $V\in C^2(M)$ such that $\mu({\rm d} x):={\rm e}^{V(x)}{\rm d} x$ is a probability measure, and let $X_t$ be the diffusion process generated…

Probability · Mathematics 2022-04-11 Feng-Yu Wang

Using the dual formulation only, we show that the regularity of unbalanced optimal transport also called entropy-transport inherits from the regularity of standard optimal transport. We provide detailed examples of Riemannian manifolds and…

Optimization and Control · Mathematics 2024-07-02 Thomas Gallouët , Roberta Ghezzi , François-Xavier Vialard

The problem of eliminating fast-relaxing variables to obtain an effective drift-diffusion process in position is solved in a uniform and straightforward way for models with velocity a function jointly of position and fast variables. A more…

Statistical Mechanics · Physics 2019-11-13 Paul E. Lammert

We develop a new class of path transformations for one-dimensional diffusions that are tailored to alter their long-run behaviour from transient to recurrent or vice versa. This immediately leads to a formula for the distribution of the…

Probability · Mathematics 2018-02-02 Umut Çetin

We consider singularly perturbed convection-diffusion equations on one-dimensional networks (metric graphs) as well as the transport problems arising in the vanishing diffusion limit. Suitable coupling condition at inner vertices are…

Analysis of PDEs · Mathematics 2020-04-22 Herbert Egger , Nora Philippi

For a class of (non-symmetric) diffusion processes on a length space, which in particular include the (reflecting) diffusion processes on a connected compact Riemannian manifold, the exact convergence rate is derived for $({\mathbb E}…

Probability · Mathematics 2024-08-20 Feng-Yu Wang , Bingyao Wu , Jie-Xiang Zhu

In this paper, we study the optimal transport problem induced by separable cost functions. In this framework, transportation can be expressed as the composition of two lower-dimensional movements. Through this reformulation, we prove that…

Optimization and Control · Mathematics 2021-05-18 Gennaro Auricchio

Rectified flow (Liu et al., 2022; Liu, 2022; Wu et al., 2023) is a method for defining a transport map between two distributions, and enjoys popularity in machine learning, although theoretical results supporting the validity of these…

Statistics Theory · Mathematics 2025-12-11 Gonzalo Mena , Arun Kumar Kuchibhotla , Larry Wasserman

Diffusion Models (DMs) have achieved remarkable progress in generative modeling. However, the mismatch between the forward terminal distribution and reverse initial distribution introduces prior error, leading to deviations of sampling…

Machine Learning · Computer Science 2026-02-06 Zhanpeng Wang , Shenghao Li , Jiameng Che , Chen Wang , Shangling Jui , Na Lei , Zhongxuan Luo

Diffusion Bridge and Flow Matching have both demonstrated compelling empirical performance in transformation between arbitrary distributions. However, there remains confusion about which approach is generally preferable, and the substantial…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Kaizhen Zhu , Mokai Pan , Zhechuan Yu , Jingya Wang , Jingyi Yu , Ye Shi

We discuss transportation cost inequalities for uniform measures on convex bodies, and connections with other geometric and functional inequalities. In particular, we show how transportation inequalities can be applied to the slicing…

Metric Geometry · Mathematics 2008-02-08 Mark W. Meckes

This paper intents to present the state of art and recent developments of the optimal transportation theory with many marginals for a class of repulsive cost functions. We introduce some aspects of the Density Functional Theory (DFT) from a…

Analysis of PDEs · Mathematics 2015-12-02 Simone Di Marino , Augusto Gerolin , Luca Nenna

Consider transportation of one distribution of mass onto another, chosen to optimize the total expected cost, where cost per unit mass transported from x to y is given by a smooth function c(x,y). If the source density f^+(x) is bounded…

Analysis of PDEs · Mathematics 2011-07-07 Alessio Figalli , Young-Heon Kim , Robert J. McCann

For one-dimensional growth processes we consider the distribution of the height above a given point of the substrate and study its scale invariance in the limit of large times. We argue that for self-similar growth from a single seed the…

Statistical Mechanics · Physics 2009-10-31 Michael Praehofer , Herbert Spohn

We study the escape rate of diffusion process with two approaches. We first give an upper rate function for the diffusion process associated with a symmetric, strongly local regular Dirichlet form. The upper rate function is in terms of the…

Probability · Mathematics 2013-10-16 Shunxiang Ouyang

We introduce the transportation-annihilation distance $W_p^\sharp$ between subprobabilities and derive contraction estimates with respect to this distance for the heat flow with homogeneous Dirichlet boundary conditions on an open set in a…

Analysis of PDEs · Mathematics 2020-05-05 Angelo Profeta , Karl-Theodor Sturm

One of the most well-known results in the theory of optimal transportation is the equivalence between the convexity of the entropy functional with respect to the Riemannian Wasserstein metric and the Ricci curvature lower bound of the…

Differential Geometry · Mathematics 2013-07-23 Paul W. Y. Lee

A nonnegative integer matrix is said to be width-one if its nonzero entries lie along a path consisting of steps to the south and to the east. These matrices are important in optimal transport theory: the northwest corner algorithm, for…

Combinatorics · Mathematics 2023-08-21 William Q. Erickson , Jan Kretschmann

In the present paper, we prove that the Wasserstein distance on the space of continuous sample-paths equipped with the supremum norm between the laws of a uniformly elliptic one-dimensional diffusion process and its Euler discretization…

Probability · Mathematics 2014-04-29 A. Alfonsi , B. Jourdain , A. Kohatsu-Higa

In this work, we study the task of distributed optimization over a network of learners in which each learner possesses a convex cost function, a set of affine equality constraints, and a set of convex inequality constraints. We propose a…

Optimization and Control · Mathematics 2015-06-18 Zaid J. Towfic , Ali H. Sayed
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