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In 2010, Bezuglyi, Kwiatkowski, Medynets and Solomyak [Ergodic Theory Dynam. Systems 30 (2010), no.4, 973-1007] found a complete description of the set of probability ergodic tail invariant measures on the path space of a standard…

Dynamical Systems · Mathematics 2024-02-28 Sergey Bezuglyi , Olena Karpel , Jan Kwiatkowski

Diffusion models (DMs) excel in unconditional generation, as well as on applications such as image editing and restoration. The success of DMs lies in the iterative nature of diffusion: diffusion breaks down the complex process of mapping…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Beomsu Kim , Jaemin Kim , Jeongsol Kim , Jong Chul Ye

We derive an integration by parts formula for functionals of determinantal processes on compact sets, completing the arguments of [4]. This is used to show the existence of a configuration-valued diffusion process which is non-colliding and…

Probability · Mathematics 2015-09-30 Laurent Decreusefond , Ian Flint , Nicolas Privault , Giovanni Luca Torrisi

We present a path integral formulation of Darcy's equation in one dimension with random permeability described by a correlated multi-variate lognormal distribution. This path integral is evaluated with the Markov chain Monte Carlo method to…

Computational Physics · Physics 2018-04-18 Marise J. E. Westbroek , Gil-Arnaud Coche , Peter R. King , Dimitri D. Vvedensky

Positive recurrence of a $d$-dimensional diffusion with switching and with one recurrent and one transient regimes and variable switching intensities is established under suitable conditions. The approach is based on embedded Markov chains.

Probability · Mathematics 2023-01-02 Alexander Veretennikov

We derive a minimalist but powerful deterministic denoising-diffusion model. While denoising diffusion has shown great success in many domains, its underlying theory remains largely inaccessible to non-expert users. Indeed, an understanding…

Graphics · Computer Science 2023-05-08 Eric Heitz , Laurent Belcour , Thomas Chambon

Score-matching generative models have proven successful at sampling from complex high-dimensional data distributions. In many applications, this distribution is believed to concentrate on a much lower $d$-dimensional manifold embedded into…

Machine Learning · Statistics 2025-04-25 Peter Potaptchik , Iskander Azangulov , George Deligiannidis

We give necessary and sufficient conditions to characterize the convergence in distribution of a sequence of arbitrary random variables to a probability distribution which is the invariant measure of a diffusion process. This class of…

Probability · Mathematics 2015-11-13 Seiichiro Kusuoka , Ciprian Tudor

In the Lorentz mirror walk in dimension $d\geq 2$, mirrors are randomly placed on the vertices of $\mathbb{Z}^d$ at density $p\in[0,1]$. A light ray is then shot from the origin and deflected through the various mirrors in space. The object…

Probability · Mathematics 2025-07-03 Dor Elboim , Antoine Gloria , Felipe Hernández

This paper is devoted to the development of a theoretical and computational framework to efficiently sample the statistically significant thermally activated reaction pathways, in multi-dimensional systems obeying Langevin dynamics. We show…

Statistical Mechanics · Physics 2009-11-13 E. Autieri , P. Faccioli , M. Sega , F. Pederiva , H. Orland

We study the long time behavior (homogenization) of a diffusion in random medium with time and space dependent coefficients. The diffusion coefficient may degenerate. In Stochastic Process. Appl. (2007) (to appear), an invariance principle…

Probability · Mathematics 2008-08-26 Rémi Rhodes

For continuous \gamma, g:[0,1]\to(0,\infty), consider the degenerate stochastic differential equation dX_t=[1-|X_t|^2]^{1/2}\gamma(|X_t|) dB_t-g(|X_t|)X_t dt in the closed unit ball of R^n. We introduce a new idea to show pathwise…

Probability · Mathematics 2007-05-23 Dante DeBlassie

Breakpoint graphs are ubiquitous structures in the field of genome rearrangements. Their cycle decomposition has proved useful in computing and bounding many measures of (dis)similarity between genomes, and studying the distribution of…

Discrete Mathematics · Computer Science 2013-03-18 Simona Grusea , Anthony Labarre

Score-based diffusion models have recently emerged as state-of-the-art generative models for a variety of data modalities. Nonetheless, it remains unclear how to adapt these models to generate long multivariate time series. Viewing a time…

Machine Learning · Computer Science 2025-02-28 Barbora Barancikova , Zhuoyue Huang , Cristopher Salvi

Transition path theory (TPT) for diffusion processes is a framework for analysing the transitions of multiscale ergodic diffusion processes between disjoint metastable subsets of state space. Most methods for applying TPT involve the…

Numerical Analysis · Mathematics 2021-03-31 Nada Cvetković , Tim Conrad , Han Cheng Lie

We give a generalization to a continuous setting of the classic Markov chain tree Theorem. In particular, we consider an irreducible diffusion process on a metric graph. The unique invariant measure has an atomic component on the vertices…

Probability · Mathematics 2020-02-04 Michele Aleandri , Matteo Colangeli , Davide Gabrielli

The signature transform, which is defined in terms of iterated path integrals of all orders, provides a faithful representation of the group of tree-reduced geometric rough paths. While the signature coefficients are known to decay…

Probability · Mathematics 2025-06-24 Horatio Boedihardjo , Xi Geng , Sheng Wang

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

We establish a simple criterion for locating points where the transition density of a degenerate diffusion is strictly positive. Throughout, we assume that the diffusion satisfies a stochastic differential equation (SDE) on $\mathbf{R}^d$…

Probability · Mathematics 2017-04-11 David P. Herzog , Jonathan C. Mattingly

The signature of a parametric curve is a sequence of tensors whose entries are iterated integrals. This construction is central to the theory of rough paths in stochastic analysis. It is here examined through the lens of algebraic geometry.…

Probability · Mathematics 2019-12-04 Carlos Améndola , Peter Friz , Bernd Sturmfels