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Stein variational gradient descent (SVGD) refers to a class of methods for Bayesian inference based on interacting particle systems. In this paper, we consider the originally proposed deterministic dynamics as well as a stochastic variant,…

Machine Learning · Statistics 2021-02-26 Nikolas Nüsken , D. R. Michiel Renger

A constructive numerical approximation of the two-dimensional unsteady stochastic Navier-Stokes equations of an incompressible fluid is proposed via a pseudo-compressibility technique involving a parameter $\epsilon$. Space and time are…

Numerical Analysis · Mathematics 2022-05-02 Jad Doghman

In this paper, we study the asymptotic behaviors of solutions to the inhomogeneous Navier-Stokes-Vlasov system in $\mathbb{R}^{3}\times\mathbb{R}^{3}$, where the initial fluid density is allowed to vanish. We establish the uniform bound of…

Analysis of PDEs · Mathematics 2025-05-12 Hai-Liang Li , Ling-Yun Shou , Yue Zhang

We introduce a stochastic fractional calculus. As an application, we present a stochastic fractional calculus of variations, which generalizes the fractional calculus of variations to stochastic processes. A stochastic fractional…

Optimization and Control · Mathematics 2020-08-10 Houssine Zine , Delfim F. M. Torres

This paper presents a new numerical method for the compressible Navier-Stokes equations governing the flow of an ideal isentropic gas. To approximate the continuity equation, the method utilizes a discontinuous Galerkin discretization on…

Numerical Analysis · Mathematics 2012-06-21 Trygve K. Karper

We consider an SDE in R^m of the type dX(t)=a(X(t))dt+dU(t) with a L\'evy process U and study the problem for the distribution of a solution to be regular in various senses. We do not impose any specific conditions on the L\'evy measure of…

Probability · Mathematics 2007-05-23 Alexey Kulik

Stochastic geometric mechanics (SGM) is known for its potential utility in quantifying uncertainty in global climate modelling of the Earth's ocean and atmosphere while also preserving the fundamental advective transport properties of ideal…

Fluid Dynamics · Physics 2023-08-30 Darryl D. Holm , Erwin Luesink

We present a novel Type II variational principle on the cotangent bundle of a Lie group which enforces Type II boundary conditions, i.e., fixed initial position and final momentum. In general, such Type II variational principles are only…

Numerical Analysis · Mathematics 2025-02-19 Brian K. Tran , Melvin Leok

We develop a dynamical systems theory for the compressible Navier-Stokes equations based on global in time weak solutions. The following questions will be addressed: Global existence and critical values of the adiabatic constant;…

Dynamical Systems · Mathematics 2007-05-23 Eduard Feireisl

We study the full Navier--Stokes--Fourier system governing the motion of a general viscous, heat-conducting, and compressible fluid subject to stochastic perturbation. Stochastic effects are implemented through (i) random initial data, (ii)…

Analysis of PDEs · Mathematics 2017-10-31 Dominic Breit , Eduard Feireisl

We introduce a concept of dissipative measure valued martingale solutions for stochastic compressible Navier-Stokes equations. These solutions are weak from a probabilistic perspective, since they include both the driving Wiener process and…

Probability · Mathematics 2025-08-07 Utsab Sarkar

Inspired by the Clebsch optimal control problem, we introduce a new variational principle that is suitable for capturing the geometry of relativistic field theories with constraints related to a gauge symmetry. Its special feature is that…

Mathematical Physics · Physics 2019-09-04 Tobias Diez , Gerd Rudolph

Variational formulations for viscous flows which lead to the Navier-Stokes equation are examined. Since viscosity leads to dissipation and, therefore, to the irreversible transfer of mechanical energy to heat, thermal degrees of freedom…

Fluid Dynamics · Physics 2023-04-06 Sylvio R. Bistafa

We present stochastic homogenization results for viscous Hamilton-Jacobi equations using a new argument which is based only on the subadditive structure of maximal subsolutions (solutions of the "metric problem"). This permits us to give…

Analysis of PDEs · Mathematics 2016-01-20 Scott N. Armstrong , Hung V. Tran

The generalized polynomial chaos method is applied to the Buckley-Leverett equation. We consider a spatially homogeneous domain modeled as a random field. The problem is projected onto stochastic basis functions which yields an extended…

Numerical Analysis · Mathematics 2016-08-24 Per Pettersson , Hamdi A. Tchelepi

We propose a concept of dissipative weak (DW) solutions for the Navier-Stokes-Korteweg (NSK) system and prove conditional convergence of a structure-preserving finite volume scheme towards such a solution. DW solutions provide a generalized…

Numerical Analysis · Mathematics 2026-04-20 Jan Giesselmann , Philipp Öffner , Robert Sauerborn

We propose a formalization for dissipative fluids with interfaces in an inhomogeneous temperature field from the viewpoint of a variational principle. Generally, the Lagrangian of a fluid is given by the kinetic energy density minus the…

Fluid Dynamics · Physics 2015-07-10 Hiroki Fukagawa , Chun Liu , Takeshi Tsuji

Homogenisation theory has seen recent applications in deriving stochastic transport models for fluid dynamics. In this work, we first derive the stochastic Lagrange-to-Euler map that underpins stochastic transport noise in fluid dynamics as…

Mathematical Physics · Physics 2025-11-06 Theo Diamantakis , Ruiao Hu , James-Michael Leahy

A new method is described for constructing a generalized solution for stochastic differential equations. The method is based on the Cameron-Martin version of the Wiener Chaos expansion and provides a unified framework for the study of…

Probability · Mathematics 2007-05-23 S. V. Lototsky , B. L. Rozovskii

This work is based on a formulation of the incompressible Navier-Stokes equations developed by P. Constantin and G.Iyer, where the velocity field of a viscous incompressible fluid is written as the expected value of a stochastic process. If…

Probability · Mathematics 2017-09-07 Alexei Novikov , Karim Shikh Khalil
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