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Convergence of stochastic processes with jumps to diffusion processes is investigated in the case when the limit process has discontinuous coefficients. An example is given in which the diffusion approximation of a queueing model yields a…

Probability · Mathematics 2016-09-07 N. V. Krylov , R. Liptser

This paper presents a unified framework for uncertainty propagation in dynamical systems involving hybrid aleatory and epistemic uncertainties. The framework accommodates precise probabilistic, imprecise probabilistic, and non-probabilistic…

Methodology · Statistics 2025-09-12 Yi Luo , Meng-Ze Lyu , Matteo Broggi , Marko Thiele , Vasileios C. Fragkoulis , Michael Beer

Generative diffusion models have achieved remarkable success in producing high-quality images. However, these models typically operate in continuous intensity spaces, diffusing independently across pixels and color channels. As a result,…

Graphics · Computer Science 2025-05-20 Javier E. Santos , Agnese Marcato , Roman Colman , Nicholas Lubbers , Yen Ting Lin

Despite the fact that the theory of mixtures has been part of non-equilibrium thermodynamics and engineering for a long time, it is far from complete. While it is well formulated and tested in the case of mechanical equilibrium (where only…

Statistical Mechanics · Physics 2022-07-01 Petr Vágner , Michal Pavelka , Jürgen Fuhrmann , Václav Klika

Driven by diverse applications, several recent models impose randomly switching boundary conditions on either a PDE or SDE. The purpose of this paper is to provide tools for calculating statistics of these models and to establish a…

Probability · Mathematics 2020-03-13 Sean D. Lawley

We establish a process level large deviation principle for systems of interacting Bessel-like diffusion processes. By establishing weak uniqueness for the limiting non-local SDE of McKean-Vlasov type, we conclude that the latter describes…

Probability · Mathematics 2013-03-14 Tomoyuki Ichiba , Mykhaylo Shkolnikov

In this paper, we establish smoothness of moments of the solutions of discrete coagulation-diffusion systems. As key assumptions, we suppose that the coagulation coefficients grow at most sub-linearly and that the diffusion coefficients…

Analysis of PDEs · Mathematics 2015-11-19 Maxime Breden , Laurent Desvillettes , Klemens Fellner

Diffusion models are mainly studied on image data. However, non-image data (e.g., tabular data) are also prevalent in real applications and tend to be noisy due to some inevitable factors in the stage of data collection, degrading the…

Machine Learning · Computer Science 2024-10-04 Yangming Li , Max Ruiz Luyten , Mihaela van der Schaar

In this paper we investigate jump-diffusion processes in random environments which are given as the weak solutions to SDE's. We formulate conditions ensuring existence and uniqueness in law of solutions. We investigate Markov property. To…

Probability · Mathematics 2013-07-19 Jacek Jakubowski , Mariusz Niewęgłowski

We introduce a lattice random walk discretisation scheme for stochastic differential equations (SDEs) that samples binary or ternary increments at each step, suppressing complex drift and diffusion computations to simple 1 or 2 bit random…

Numerical Analysis · Mathematics 2026-02-18 Samuel Duffield , Maxwell Aifer , Denis Melanson , Zach Belateche , Patrick J. Coles

We consider a multicontinuum model in porous media applications, which is described as a system of coupled flow equations. The coupling between different continua depends on many factors and its modeling is important for porous media…

Probability · Mathematics 2020-01-27 Hakima Bessaih , Razvan Florian Maris

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

We consider a large market model of defaultable assets in which the asset price processes are modelled as Heston-type stochastic volatility models with default upon hitting a lower boundary. We assume that both the asset prices and their…

Probability · Mathematics 2019-05-15 Ben Hambly , Nikolaos Kolliopoulos

This paper provides a systematic method to build wind speed models based on stochastic differential equations (SDEs). The resulting models produce stochastic processes with a given probability distribution and exponential decaying…

Applications · Statistics 2015-11-10 Rafael Zárate Miñano , Federico Milano

We derive a new, exact and transparent expansion for option smiles, which lends itself both to analytical approximation and, perhaps more importantly, to congenial numerical treatments. We show that the skew and the curvature of the smile…

Pricing of Securities · Quantitative Finance 2012-04-25 L. De Leo , V. Vargas , S. Ciliberti , J. -P. Bouchaud

Delattre et al. (2013) considered a system of stochastic differential equations (SDEs) in a random effects setup. Under the independent and identical (iid) situation, and assuming normal distribution of the random effects, they established…

Statistics Theory · Mathematics 2020-05-04 Trisha Maitra , Sourabh Bhattacharya

Diffusion coefficients are key thermophysical properties for modeling mass transport in liquids, but experimental data are scarce, making reliable prediction methods indispensable. In the present work, we introduce a new method for…

This article studies the fluctuation behaviour of the stochastic point vortex model with common noise. Using the martingale method combined with a localization argument, we prove that the sequence of fluctuation processes converges in…

Probability · Mathematics 2025-01-14 Yufei Shao , Xianliang Zhao

We introduce a simple and efficient algorithm for diffusion in smoothed particle hydrodynamics (SPH) simulations and apply it to the problem of chemical mixing. Based on the concept of turbulent diffusion, we link the diffusivity of a…

Astrophysics · Physics 2009-11-13 Thomas H. Greif , Simon C. O. Glover , Volker Bromm , Ralf S. Klessen

Diffusion-based generative models use stochastic differential equations (SDEs) and their equivalent ordinary differential equations (ODEs) to establish a smooth connection between a complex data distribution and a tractable prior…

Machine Learning · Computer Science 2024-08-25 Defang Chen , Zhenyu Zhou , Can Wang , Chunhua Shen , Siwei Lyu