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In this paper we investigate the regularity properties of strong solutions to SDEs driven by L\'evy processes with irregular drift coefficients. Under some mild conditions, we show that the singular SDE has a unique strong solution for each…

Probability · Mathematics 2021-03-17 Guohuan Zhao

A general purely crystalline mean curvature flow equation with a nonuniform driving force term is considered. The unique existence of a level set flow is established when the driving force term is continuous and spatially Lipschitz…

Analysis of PDEs · Mathematics 2020-06-09 Yoshikazu Giga , Norbert Pozar

Statistical solutions of incompressible Euler describe turbulent dynamics as time-parameterized laws on $L^2$ whose multi-point correlations satisfy an infinite hierarchy of weak identities. Modern generative samplers for PDE forecasting…

Analysis of PDEs · Mathematics 2026-02-24 Victor Armegioiu

Since the breakthrough in rough paths theory for stochastic ordinary differential equations (SDEs), there has been a strong interest in investigating the rough differential equation (RDE) approach and its numerous applications. Rough path…

Probability · Mathematics 2021-04-26 Christian Kuehn , Alexandra Neamtu

We review the construction and analysis of numerical methods for strongly nonlinear PDEs, with an emphasis on convex and nonconvex fully nonlinear equations and the convergence to viscosity solutions. We begin by describing a fundamental…

Numerical Analysis · Mathematics 2016-10-26 Michael Neilan , Abner J. Salgado , Wujun Zhang

This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average of the fast variable and assuming the boundary…

Systems and Control · Computer Science 2018-09-24 Mohammad Deghat , Saeed Ahmadizadeh , Dragan Nesic , Chris Manzie

We deduce stability and pathwise uniqueness for a McKean-Vlasov equation with random coefficients and a multidimensional Brownian motion as driver. Our analysis focuses on a non-Lipschitz drift coefficient and includes moment estimates for…

Probability · Mathematics 2024-08-21 Alexander Kalinin , Thilo Meyer-Brandis , Frank Proske

This paper establishes the existence and uniqueness of solutions for rough differential equations driven by reduced rough paths with low regularity, specifically in the roughness regime $\frac{1}{3} < \alpha \leq \frac{1}{2}$. While the…

Probability · Mathematics 2025-12-02 Nannan Li , Xing Gao

We prove the existence of a solution to an equation governing the number density within a compact domain of a discrete particle system for a prescribed class of particle interactions taking into account the effects of the diffusion and…

Probability · Mathematics 2007-05-23 Clive G. Wells

We prove existence and uniqueness of strong solutions, as well as continuous dependence on the initial datum, for a class of fully nonlinear second-order stochastic PDEs with drift in divergence form. Due to rather general assumptions on…

Analysis of PDEs · Mathematics 2018-10-03 Carlo Marinelli , Luca Scarpa

In this paper, the existence of smooth positive solutions to a Robin boundary-value problem with non-homogeneous differential operator and reaction given by a nonlinear convection term plus a singular one is established. Proofs chiefly…

Analysis of PDEs · Mathematics 2019-09-24 Umberto Guarnotta , Salvatore A. Marano , Dumitru Motreanu

The nonlinear rheological properties of dense colloidal suspensions under steady shear are discussed within a first principles approach. It starts from the Smoluchowski equation of interacting Brownian particles in a given shear flow,…

Soft Condensed Matter · Physics 2008-10-15 Matthias Fuchs

In this study, we consider a linearized compressible flow structure interaction PDE model for which the interaction interface is under the effect of material derivative term. While the linearization takes place around a constant pressure…

Analysis of PDEs · Mathematics 2021-02-09 Pelin Guven Geredeli

We develop a framework that systematically casts the solvability and uniqueness conditions of linearized geometric boundary-value problems into cohomological terms. The theory is designed to be applicable without assumptions on the…

Differential Geometry · Mathematics 2026-03-16 Roee Leder

We consider flows of ordinary differential equations (ODEs) driven by path differentiable vector fields. Path differentiable functions constitute a proper subclass of Lipschitz functions which admit conservative gradients, a notion of…

Machine Learning · Computer Science 2022-01-12 Swann Marx , Edouard Pauwels

Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method…

Probability · Mathematics 2020-11-25 Martin Hutzenthaler , Arnulf Jentzen

Comparing and recognizing metrics can be extraordinarily difficult because of the group of diffeomorphisms. Two metrics, that could even be the same, could look completely different in different coordinates. This is the gauge problem. The…

Differential Geometry · Mathematics 2025-09-22 Tobias Holck Colding , William P. Minicozzi

We construct a deterministic, Lagrangian many-particle approximation to a class of nonlocal transport PDEs with nonlinear mobility arising in many contexts in biology and social sciences. The approximating particle system is a nonlocal…

Analysis of PDEs · Mathematics 2018-01-29 M. Di Francesco , S. Fagioli , E. Radici

In this paper we focus on nonlinear SPDEs with singularities included in both drift and noise coefficients, for which the Gelfand-triple argument developed for (local) monotone SPDEs turns out to be invalid. We propose a general framework…

Analysis of PDEs · Mathematics 2023-06-06 Hao Tang , Feng-Yu Wang

Recovering continuous-time dynamics from discrete observations is difficult because local supervision (e.g., pointwise regression targets, derivative approximations, or equation residuals) loses fidelity as the observation interval grows.…

Machine Learning · Computer Science 2026-05-12 Yuxiang Luo , Andrew Perrault