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Related papers: Diffusion Approximations to Schr\"{o}dinger Bridge…

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Motivated by modern machine learning applications where we only have access to empirical measures constructed from finite samples, we relax the marginal constraints of the classical Schr\"odinger bridge problem by penalizing the transport…

Probability · Mathematics 2026-02-10 Yifan Jiang , Renyuan Xu , Luhao Zhang

Schr\"{o}dinger bridge is a stochastic optimal control problem to steer a given initial state density to another, subject to controlled diffusion and deadline constraints. A popular method to numerically solve the Schr\"{o}dinger bridge…

Optimization and Control · Mathematics 2023-09-14 Alexis M. H. Teter , Yongxin Chen , Abhishek Halder

We study the weak approximation error of a skew diffusion with bounded measurable drift and H\"older diffusion coefficient by an Euler-type scheme, which consists of iteratively simulating skew Brownian motions with constant drift. We first…

Probability · Mathematics 2016-09-30 Noufel Frikha

Diffusion models are recent state-of-the-art methods for image generation and likelihood estimation. In this work, we generalize continuous-time diffusion models to arbitrary Riemannian manifolds and derive a variational framework for…

Machine Learning · Computer Science 2022-08-18 Chin-Wei Huang , Milad Aghajohari , Avishek Joey Bose , Prakash Panangaden , Aaron Courville

We study a generalization of the Brownian bridge as a stochastic process that models the position and velocity of inertial particles between the two end-points of a time interval. The particles experience random acceleration and are assumed…

Systems and Control · Computer Science 2014-07-15 Yongxin Chen , Tryphon Georgiou

In recent years, quantities derived from the heat equation have become popular in shape processing and analysis of triangulated surfaces. Such measures are often robust with respect to different kinds of perturbations, including…

Computer Vision and Pattern Recognition · Computer Science 2021-06-09 Jose A. Iglesias , Ron Kimmel

This paper introduces a dynamic formulation of divergence-regularized optimal transport with weak targets on the path space. In our formulation, the classical relative entropy penalty is replaced by a general convex divergence, and terminal…

Probability · Mathematics 2026-03-31 Camilo Hernández , Ludovic Tangpi

This paper studies rescaled images, under $\exp^{-1}_{\mu}$, of the sample Fr\'{e}chet means of i.i.d. random variables $\{X_k\vert k\geq 1\}$ with Fr\'{e}chet mean $\mu$ on a Riemannian manifold. We show that, with appropriate scaling,…

Probability · Mathematics 2015-10-26 Huiling Le

We propose an approach to compute the boundary crossing probabilities for a class of diffusion processes which can be expressed as piecewise monotone (not necessarily one-to-one) functionals of a standard Brownian motion. This class…

Probability · Mathematics 2007-05-23 Liqun Wang , Klaus Pötzelberger

This work studies the Schr\"odinger bridge problem for the kinematic equation on a compact connected Lie group. The objective is to steer a controlled diffusion between given initial and terminal densities supported over the Lie group while…

Optimization and Control · Mathematics 2026-03-23 Hamza Mahmood , Abhishek Halder , Adeel Akhtar

We discuss a family of time-inhomogeneous two-dimensional diffusions, defined over a finite time interval $[0,T]$, having transition density functions that are expressible in terms of the integral kernels for negative exponentials of the…

Probability · Mathematics 2023-07-04 Jeremy Clark , Barkat Mian

In this article we consider a family of real-valued diffusion processes on the time interval $[0,1]$ indexed by their prescribed initial value $x \in \mathbb{R}$ and another point in space, $y \in \mathbb{R}$. We first present an…

Probability · Mathematics 2019-06-03 Florian Hildebrandt , Sylvie Rœlly

Density ratio estimation is fundamental to tasks involving $f$-divergences, yet existing methods often fail under significantly different distributions or inadequately overlapping supports -- the density-chasm and the support-chasm…

Machine Learning · Computer Science 2025-11-04 Wei Chen , Shigui Li , Jiacheng Li , Junmei Yang , John Paisley , Delu Zeng

We consider the problem to identify the most likely flow in phase space, of (inertial) particles under stochastic forcing, that is in agreement with spatial (marginal) distributions that are specified at a set of points in time. The…

Optimization and Control · Mathematics 2019-02-25 Yongxin Chen , Giovanni Conforti , Tryphon T. Georgiou , Luigia Ripani

We show that geodesic random walks on a complete Finsler manifold of bounded geometry converge to a diffusion process which is, up to a drift, the Brownian motion corresponding to a Riemannian metric.

Differential Geometry · Mathematics 2022-12-07 Tianyu Ma , Vladimir S. Matveev , Ilya Pavlyukevich

Learning the distribution of data on Riemannian manifolds is crucial for modeling data from non-Euclidean space, which is required by many applications in diverse scientific fields. Yet, existing generative models on manifolds suffer from…

Machine Learning · Computer Science 2024-06-04 Jaehyeong Jo , Sung Ju Hwang

We approximate the heat kernel $h(x,y,t)$ on a compact connected Riemannian manifold $M$ without boundary uniformly in $(x,y,t)\in M\times M\times [a,b]$, $a>0$, by $n$-fold integrals over $M^n$ of the densities of Brownian bridges.…

Probability · Mathematics 2020-03-03 Evelina Shamarova , Alexandre B. Simas

We develop two-dimensional Brownian dynamics simulations to examine the motion of disks under thermal fluctuations and Hookean forces. Our simulations are designed to be experimental-like, since the experimental conditions define the…

Soft Condensed Matter · Physics 2017-05-26 Manuel Pancorbo , Miguel A. Rubio , P. Domínguez-García

Quantum counterparts of Schrodinger's classical bridge problem have been around for the better part of half a century. During that time, several quantum approaches to this multifaceted classical problem have been introduced. In the present…

Quantum Physics · Physics 2025-03-11 Olga Movilla Miangolarra , Ralph Sabbagh , Tryphon T. Georgiou

We study generative modeling for time series using entropic optimal transport and the Schr\"odinger bridge (SB) framework, with a focus on applications in finance and energy modeling. Extending the diffusion-based approach of Hamdouche,…

Mathematical Finance · Quantitative Finance 2026-02-24 Stefano De Marco , Huyên Pham , Davide Zanni