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The random measures on the space of continuous functions are considered. Stationary random measures are described. The weak solutions of the stochastic equations are substituted by the strong measure-valued solutions.

Probability · Mathematics 2007-05-23 A. A. Dorogovtsev

While stochastic variational inference is relatively well known for scaling inference in Bayesian probabilistic models, related methods also offer ways to circumnavigate the approximation of analytically intractable expectations. The key…

Machine Learning · Statistics 2015-09-08 David A. Knowles

In uncertainty quantification, a stochastic modelling is often applied, where parameters are substituted by random variables. We investigate linear dynamical systems of ordinary differential equations with a quantity of interest as output.…

Numerical Analysis · Mathematics 2019-09-23 Roland Pulch , Akil Narayan

We study the well-posedness of the Cauchy problem for a fractional porous medium equation with a varying density. We establish existence of weak energy solutions; uniqueness and nonuniqueness is studied as well, according with the behavior…

Analysis of PDEs · Mathematics 2013-02-04 Fabio Punzo , Gabriele Terrone

The construction of loss functions presents a major challenge in data-driven modeling involving weak-form operators in PDEs and gradient flows, particularly due to the need to select test functions appropriately. We address this challenge…

Machine Learning · Statistics 2025-12-16 Yuan Gao , Quanjun Lang , Fei Lu

We prove existence of weak solutions for a diffuse interface model for the flow of two viscous incompressible Newtonian fluids with different densities in a bounded domain in two and three space dimensions. In contrast to previous works, we…

Analysis of PDEs · Mathematics 2019-11-21 Helmut Abels , Yutaka Terasawa

We investigate the approximate dynamics of several differential equations when the solutions are restricted to a sparse subset of a given basis. The restriction is enforced at every time step by simply applying soft thresholding to the…

Numerical Analysis · Mathematics 2015-06-12 Hayden Schaeffer , Stanley Osher , Russel Caflisch , Cory Hauck

In this paper, a systematic approach of constructing modified equations for weak stochastic symplectic methods of stochastic Hamiltonian systems is given via using the generating functions of the stochastic symplectic methods. This approach…

Numerical Analysis · Mathematics 2014-11-11 Lijin Wang , Jialin Hong

The technique of stochastic solutions, previously used for deterministic equations, is here proposed as a solution method for partial differential equations driven by distribution-valued noises.

Probability · Mathematics 2024-08-22 R. Vilela Mendes

We consider a stochastic delay differential equation driven by a Holder continuous process and a Wiener process. Under fairly general assumptions on its coefficients, we prove that this equation is uniquely solvable. We also give sufficient…

Probability · Mathematics 2013-10-09 Georgiy Shevchenko

We introduce a simple but powerful technique to study processes driven by two or more reinforcement mechanisms in competition. We apply our method to two types of models: to non conservative zero range processes on finite graphs, and to…

Probability · Mathematics 2022-06-30 Dirk Erhard , Guilherme Reis

We prove the global-in-time existence of nonnegative weak solutions to a class of fourth order partial differential equations on a convex bounded domain in arbitrary spatial dimensions. Our proof relies on the formal gradient flow structure…

Analysis of PDEs · Mathematics 2015-07-21 Daniel Loibl , Daniel Matthes , Jonathan Zinsl

In probability theory, how to approximate the solution of a stochastic differential equation is an important topic. In Watanabe's classical textbook, by an approximation of the Wiener process, solutions of approximated equations converge to…

Probability · Mathematics 2026-04-28 Xi Lin

The global existence of martingale solutions to the compressible Navier-Stokes equations driven by stochastic external forces, with density-dependent viscosity and vacuum, is established in this paper. This work can be regarded as a…

Analysis of PDEs · Mathematics 2024-07-30 Yachun Li , Lizhen Zhang

As a general rule, differential equations driven by a multi-dimensional irregular path $\Gamma$ are solved by constructing a rough path over $\Gamma$. The domain of definition ? and also estimates ? of the solutions depend on upper bounds…

Probability · Mathematics 2009-05-07 Jérémie Unterberger

The steady compressible Navier--Stokes--Fourier system is considered, with either Dirichlet or Navier boundary conditions for the velocity and the heat flux on the boundary proportional to the difference of the temperature inside and…

Analysis of PDEs · Mathematics 2015-11-23 Piotr B. Mucha , Milan Pokorný , Ewelina Zatorska

In this work the existence of weak solutions for a class of non-Newtonian viscous fluid problems is analyzed. The problem is modeled by the steady case of the generalized Navier-Stokes equations, where the exponent $q$ that characterizes…

Analysis of PDEs · Mathematics 2012-04-02 Hermenegildo Borges de Oliveira

We prove existence of weak solutions and weak-strong uniqueness for a mathematical model which couples the evolution of a phase-parameter $\varphi$ satisfying a Cahn-Hilliard type relation with the one of an additional variable $\sigma$…

Analysis of PDEs · Mathematics 2026-04-21 Robert Lasarzik , Elisabetta Rocca , Giulio Schimperna

We propose a suitable analytical framework to perform numerical analysis of problems arising in compressible fluid models with uncertain data. We discuss both weak and strong stochastic approach, where the former is based on the knowledge…

Analysis of PDEs · Mathematics 2022-08-24 Eduard Feireisl

This paper deals with a dynamic Gao beam of infinite length subjected to a moving concentrated Dirac mass. Under appropriate regularity assumptions on the initial data, the problem possesses a weak solution which is obtained as the limit of…

Analysis of PDEs · Mathematics 2024-05-21 Olena Atlasiuk , Arnaud Heibig , Adrien Petrov
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