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Let X be a d-dimensional diffusion and M the running supremum of its first component. In this paper, we show that for any t > 0, the density (with respect to the d + 1-dimensional Lebesgue measure) of the pair (Mt, Xt) is a weak solution of…

Probability · Mathematics 2023-01-09 Laure Coutin , Monique Pontier

We introduce a general framework for solving partial differential equations (PDEs) using generative diffusion models. In particular, we focus on the scenarios where we do not have the full knowledge of the scene necessary to apply classical…

Machine Learning · Computer Science 2024-11-04 Jiahe Huang , Guandao Yang , Zichen Wang , Jeong Joon Park

The diffuse-domain, or smoothed boundary, method is an attractive approach for solving partial differential equations in complex geometries because of its simplicity and flexibility. In this method the complex geometry is embedded into a…

Numerical Analysis · Mathematics 2019-12-02 Fei Yu , Zhenlin Guo , John Lowengrub

During the upstroke of a normal eye blink, the upper lid moves and paints a thin tear film over the exposed corneal and conjunctival surfaces. This thin tear film may be modeled by a nonlinear fourth-order PDE derived from lubrication…

Numerical Analysis · Mathematics 2017-04-07 Tobin A. Driscoll , Richard J. Braun , Joseph K. Brosch

Of primary interest in this paper is the numerical approximation of a time dependent fractional, in space, diffusion equation where the domain is assumed to be nonhomogeneous, having different axial diffusion coefficients. This work is…

Numerical Analysis · Mathematics 2026-05-12 T. Catoe , V. J. Ervin

The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color…

Graphics · Computer Science 2016-10-11 Shuang Zhao , Fredo Durand , Changxi Zheng

Diffusion models have recently emerged as powerful stochastic frameworks for high-dimensional inference and generation. However, existing applications to partial differential equations (PDEs) predominantly rely on physics-informed training…

Numerical Analysis · Mathematics 2026-04-03 Yi Bing , Liu Jia , Fu Jinyang , Peng Xiang

In this work we study partial differential equations defined in a domain that moves in time according to the flow of a given ordinary differential equation, starting out of a given initial domain. We first derive a formulation for a…

Analysis of PDEs · Mathematics 2014-03-05 Manuel Fernando Cortez , Aníbal Rodríguez-Bernal

In this paper, we introduce the concept of Developmental Partial Differential Equation (DPDE), which consists of a Partial Differential Equation (PDE) on a time-varying manifold with complete coupling between the PDE and the manifold's…

Optimization and Control · Mathematics 2015-09-23 Nastassia Pouradier Duteil , Francesco Rossi , Ugo Boscain , Benedetto Piccoli

The propagation of a light ray in thin layer (film) within geometrical optics is considered. It is assumed that the ray is captured inside the layer due to reflecting walls or total internal reflection (in the case of a dielectric layer).…

Optics · Physics 2018-12-12 Tomasz Radozycki

We investigate the well-posedness of the fast diffusion equation (FDE) in a wide class of noncompact Riemannian manifolds. Existence and uniqueness of solutions for globally integrable initial data was established in [5]. However, in the…

Analysis of PDEs · Mathematics 2020-03-30 Gabriele Grillo , Matteo Muratori , Fabio Punzo

In this study, a new coupled Partial Differential Equation (CPDE) based image denoising model incorporating space-time regularization into non-linear diffusion is proposed. This proposed model is fitted with additive Gaussian noise which…

Numerical Analysis · Mathematics 2019-08-08 Subit K. Jain , Sudeb Majee , Rajendra K. Ray , Ananta K. Majee

This paper develops and analyzes a fully discrete finite element method for a class of semilinear stochastic partial differential equations (SPDEs) with multiplicative noise. The nonlinearity in the diffusion term of the SPDEs is assumed to…

Numerical Analysis · Mathematics 2018-11-22 Xiaobing Feng , Yukun Li , Yi Zhang

This work contributes to an understanding of the domain size's effect on the existence and uniqueness of the linear convection--diffusion equation with integral-type boundary conditions, where boundary conditions depend non-locally on…

Analysis of PDEs · Mathematics 2022-06-14 Chiun-Chang Lee , Masashi Mizuno , Sang-Hyuck Moon

In this work, we study a fourth order exponential equation, $u_t=\Delta e^{-\Delta u},$ derived from thin film growth on crystal surface in multiple space dimensions. We use the gradient flow method in metric space to characterize the…

Analysis of PDEs · Mathematics 2022-11-08 Yuan Gao , Jian-Guo Liu , Xin Yang Lu

Partial Differential Equations (PDEs) have long been recognized as powerful tools for image processing and analysis, providing a framework to model and exploit structural and geometric properties inherent in visual data. Over the years,…

Image and Video Processing · Electrical Eng. & Systems 2024-12-17 Alejandro Garnung Menéndez

The conditioning of the linear finite volume element discretization for general diffusion equations is studied on arbitrary simplicial meshes. The condition number is defined as the ratio of the maximal singular value of the stiffness…

Numerical Analysis · Mathematics 2020-04-20 Xiang Wang , Weizhang Huang , Yonghai Li

We prove existence of weak solutions of a fractional thin film type equation in any space dimension and for any order of the equation. The proof is based on a gradient flow technique in the space of Borel probability measures endowed with…

Analysis of PDEs · Mathematics 2020-07-02 Stefano Lisini

We analyze nonlinear degenerate coupled PDE-PDE and PDE-ODE systems that arise, for example, in the modelling of biofilm growth. One of the equations, describing the evolution of a biomass density, exhibits degenerate and singular…

Analysis of PDEs · Mathematics 2023-04-04 Koondanibha Mitra , Stefanie Sonner

The Transformer architecture has revolutionized artificial intelligence, yet a principled theoretical understanding of its internal mechanisms remains elusive. This paper introduces a novel analytical framework that reconceptualizes the…

Machine Learning · Computer Science 2025-09-30 Yukun Zhang , Xueqing Zhou