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A novel approach called Moate Simulation is presented to provide an accurate numerical evolution of probability distribution functions represented on grids arising from stochastic differential processes where initial conditions are…

Computational Finance · Quantitative Finance 2022-12-19 Michael E. Mura

Mathematical models of motility are often based on random-walk descriptions of discrete individuals that can move according to certain rules. It is usually the case that large masses concentrated in small regions of space have a great…

Physics and Society · Physics 2022-11-23 Carles Falcó

Rate processes with dynamical disorder are investigated within a simple framework provided by unidirectional electron transfer (ET) with fluctuating transfer rate. The rate fluctuations are assumed to be described by a non-Markovian…

Statistical Mechanics · Physics 2007-05-23 Igor Goychuk

A non-parametric diffusion model with an additive fractional Brownian motion noise is considered in this work. The drift is a non-parametric function that will be estimated by two methods. On one hand, we propose a locally linear estimator…

Probability · Mathematics 2014-03-13 Bruno Saussereau

This paper investigates the probability distribution of solutions to McKean--Vlasov stochastic differential equations driven by fractional Brownian motion with Hurst parameter H>1/2. Our main contribution is the derivation of the associated…

Probability · Mathematics 2026-01-12 Saloua Labed , Nacira Agram , Bernt Oksendal

The objective of this paper is to study the filtering problem for a system of partially observable processes $(X, Y)$, where $X$ is a non-Markovian pure-jump process representing the signal and $Y$ is a general jump-diffusion which provides…

Probability · Mathematics 2022-06-02 Elena Bandini , Alessandro Calvia , Katia Colaneri

Dynamic heterogeneity has often been modeled by assuming that a single-particle observable, fluctuating at a molecular scale, is influenced by its coupling to environmental variables fluctuating on a second, perhaps slower, time scale.…

Condensed Matter · Physics 2009-11-07 Gregor Diezemann , Gerald Hinze , Hans Sillescu

In this paper we study the randomized non-autonomous complete linear differential equation. The diffusion coefficient and the source term in the differential equation are assumed to be stochastic processes and the initial condition is…

Probability · Mathematics 2018-02-13 J. Catatayud , J. -C. Cortes , M. Jornet

A version of fractional diffusion on bounded domains, subject to 'homogeneous Dirichlet boundary conditions' is derived from a kinetic transport model with homogeneous inflow boundary conditions. For nonconvex domains, the result differs…

Analysis of PDEs · Mathematics 2016-07-05 Pedro Aceves-Sanchez , Christian Schmeiser

This paper introduces a new approach to generating sample paths of unknown Markovian stochastic differential equations (SDEs) using diffusion models, a class of generative AI methods commonly employed in image and video applications. Unlike…

Machine Learning · Computer Science 2026-03-17 Xuefeng Gao , Jiale Zha , Xun Yu Zhou

We address the challenge of incorporating non-Markovian electronic friction effects in quantum-mechanical approximations of dynamical observables. A generalized Langevin equation (GLE) is formulated for ring-polymer molecular dynamics…

Materials Science · Physics 2025-06-04 George Trenins , Mariana Rossi

In this note we consider generalized diffusion equations in which the diffusivity coefficient is not necessarily constant in time, but instead it solves a nonlinear fractional differential equation involving fractional Riemann-Liouville…

Probability · Mathematics 2022-09-21 Roberto Garra , Elena Issoglio , Giorgio S. Taverna

We analyze the diffusion of a Brownian particle in a fluid under stationary flow. By using the scheme of non-equilibrium thermodynamics in phase space, we obtain the Fokker-Planck equation which is compared with others derived from kinetic…

Statistical Mechanics · Physics 2016-08-16 I. Santamaría-Holek , D. Reguera , J. M. Rubí

This paper is devoted to the study of a fractional version of non-linear $\mathpzc{M}^\nu(t)$, $t>0$, linear $M^\nu (t)$, $t>0$ and sublinear $\mathfrak{M}^\nu (t)$, $t>0$ death processes. Fractionality is introduced by replacing the usual…

Probability · Mathematics 2013-04-02 Enzo Orsingher , Federico Polito , Ludmila Sakhno

This paper investigates the transient probabilistic responses of nonlinear single-degree-of-freedom oscillators subjected to external fractional Gaussian noise (FGN) excitation. Owing to the inherent long-range correlations and memory…

Probability · Mathematics 2026-05-28 Lifang Feng , Bin Pei , Yong Xu

Modern analyses of diffusion processes have proposed nonlinear versions of the Fokker-Planck equation to account for non-classical diffusion. These nonlinear equations are usually constructed on a phenomenological basis. Here we introduce a…

Statistical Mechanics · Physics 2009-11-11 Jean Pierre Boon , James F. Lutsko

We consider an operator-based latent Markov representation of a stochastic nonlinear dynamical system, where the stochastic evolution of the latent state embedded in a reproducing kernel Hilbert space is described with the corresponding…

Machine Learning · Computer Science 2026-05-08 Naichang Ke , Ryogo Tanaka , Yoshinobu Kawahara

In this paper, we study the non-linear diffusion equation associated with a particle system where the common drift depends on the rate of absorption of particles at a boundary. We provide an interpretation as a structural credit risk model…

Numerical Analysis · Mathematics 2018-08-28 Alexander Lipton , Vadim Kaushansky , Christoph Reisinger

The non-Markovian continuous-time random walk model, featuring fat-tailed waiting times and narrow distributed displacements with a non-zero mean, is a well studied model for anomalous diffusion. Using an analytical approach, we recently…

Statistical Mechanics · Physics 2023-09-18 Wanli Wang , Eli Barkai

Discrete diffusion models have emerged as powerful tools for high-quality data generation. Despite their success in discrete spaces, such as text generation tasks, the acceleration of discrete diffusion models remains under-explored. In…

Machine Learning · Computer Science 2024-12-09 Zixiang Chen , Huizhuo Yuan , Yongqian Li , Yiwen Kou , Junkai Zhang , Quanquan Gu
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