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Diffusion-based models on continuous spaces have seen substantial recent progress through the mathematical framework of gradient flows, leveraging the Wasserstein-2 (${W}_2$) metric via the Jordan-Kinderlehrer-Otto (JKO) scheme. Despite the…

Machine Learning · Computer Science 2026-04-14 Dario Rancati , Jan Maas , Francesco Locatello

Sampling from a distribution $p(x) \propto e^{-\mathcal{E}(x)}$ known up to a normalising constant is an important and challenging problem in statistics. Recent years have seen the rise of a new family of amortised sampling algorithms,…

Machine Learning · Computer Science 2026-05-29 Arran Carter , Sanghyeok Choi , Kirill Tamogashev , Víctor Elvira , Esmeralda S. Whitammer

Currently, there is no general theory for deriving diffusion approximations of queueing systems with high- or infinite-dimensional state descriptors. In this paper, we explore one path for deriving diffusion limit equations of queueing…

Probability · Mathematics 2026-05-28 Eva H Loeser

We develop a Bayesian inference method for diffusions observed discretely and with noise, which is free of discretisation bias. Unlike existing unbiased inference methods, our method does not rely on exact simulation techniques. Instead,…

Methodology · Statistics 2021-03-10 Neil K. Chada , Jordan Franks , Ajay Jasra , Kody J. H. Law , Matti Vihola

Score-based diffusion models currently constitute the state of the art in continuous generative modeling. These methods are typically formulated via overdamped or underdamped Ornstein--Uhlenbeck-type stochastic differential equations, in…

Machine Learning · Computer Science 2025-12-22 Herlock Rahimi

Progressively applying Gaussian noise transforms complex data distributions to approximately Gaussian. Reversing this dynamic defines a generative model. When the forward noising process is given by a Stochastic Differential Equation (SDE),…

Machine Learning · Statistics 2023-04-06 Valentin De Bortoli , James Thornton , Jeremy Heng , Arnaud Doucet

In this paper an exact rejection algorithm for simulating paths of the coupled Wright-Fisher diffusion is introduced. The coupled Wright-Fisher diffusion is a family of multidimensional Wright-Fisher diffusions that have drifts depending on…

Probability · Mathematics 2020-09-08 Celia García-Pareja , Henrik Hult , Timo Koski

We present a collection of explicit diffusion approximations to small temperature Schr\"{o}dinger bridges on manifolds. Our most precise results are when both marginals are the same and the Schr\"{o}dinger bridge is on a manifold with a…

Probability · Mathematics 2025-12-23 Garrett Mulcahy , Soumik Pal

This work discusses the homogenization analysis for diffusion processes on scale-free metric graphs, using weak variational formulations. The oscillations of the diffusion coefficient along the edges of a metric graph induce internal…

Analysis of PDEs · Mathematics 2016-05-31 Fernando A. Morales , Daniel E. Restrepo

We address the problem of approximating the moments of the solution, $\boldsymbol{X}(t)$, of an It\^o stochastic differential equation (SDE) with drift and a diffusion terms over a time-grid $t_0, t_1, \ldots, t_n$. In particular, we assume…

Numerical Analysis · Mathematics 2021-06-14 Albert López-Yela , Joaquin Miguez

This paper is concerned with the numerical integration of stochastic differential equations (SDEs) which govern diffusion processes driven by a standard Wiener process. With the latter being replaced by a sequence of increments at discrete…

Systems and Control · Electrical Eng. & Systems 2025-08-06 Igor G. Vladimirov

In the first part of the paper we use a new Fourier technique to obtain a Stein characterizations for random variables in the second Wiener chaos. We provide the connection between this result and similar conclusions that can be derived…

Probability · Mathematics 2016-01-14 Benjamin Arras , Ehsan Azmoodeh , Guillaume Poly , Yvik Swan

We model chaotic diffusion, in a symplectic 4D map by using the result of a theorem that was developed for stochastically perturbed integrable Hamiltonian systems. We explicitly consider a map defined by a free rotator (FR) coupled to a…

Chaotic Dynamics · Physics 2015-06-17 Martín F. Mestre , Armando Bazzani , Pablo M. Cincotta , Claudia M. Giordano

Diffusion approximations have been a popular tool for performance analysis in queueing theory, with the main reason being tractability and computational efficiency. This dissertation is concerned with establishing theoretical guarantees on…

Probability · Mathematics 2017-04-28 Anton Braverman

This work presents a comprehensive framework for enhanced diffusion modeling in fluid-structure interactions by combining the Immersed Boundary Method (IBM) with stochastic trajectories and high-order spectral boundary conditions. Using…

Analysis of PDEs · Mathematics 2024-10-31 Rômulo Damasclin Chaves dos Santos , Jorge Henrique de Oliveira Sales

Diffusion models learn to reverse the progressive noising of a data distribution to create a generative model. However, the desired continuous nature of the noising process can be at odds with discrete data. To deal with this tension…

Machine Learning · Computer Science 2023-09-13 Griffin Floto , Thorsteinn Jonsson , Mihai Nica , Scott Sanner , Eric Zhengyu Zhu

The aim of this article is to provide a scheme for simulating diffusion processes evolving in one-dimensional discontinuous media. This scheme does not rely on smoothing the coefficients that appear in the infinitesimal generator of the…

Probability · Mathematics 2007-05-23 Antoine Lejay , Miguel Martinez

One of the most fascinating phenomena observed in reaction-diffusion systems is the emergence of segregated solutions, i.e. population densities with disjoint supports. We analyse such a reaction cross-diffusion system. In order to prove…

Analysis of PDEs · Mathematics 2017-11-16 José A. Carrillo , Simone Fagioli , Filippo Santambrogio , Markus Schmidtchen

Diffusion bridge models establish probabilistic paths between arbitrary paired distributions and exhibit great potential for universal image restoration. Most existing methods merely treat them as simple variants of stochastic interpolants,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Hebaixu Wang , Jing Zhang , Haoyang Chen , Haonan Guo , Di Wang , Jiayi Ma , Bo Du

We established a new method called Discrete Weierstrass Fourier Transform, a faster and more generalized Discrete Fourier Transform, to approximate discrete data. The theory of this method as well as some experiments are analyzed in this…

Numerical Analysis · Mathematics 2016-01-07 Sheng Zhang , Brendan Harding