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Both the porous medium equation and the system of isentropic Euler equations can be considered as steepest descents on suitable manifolds of probability measures in the framework of optimal transport theory. By discretizing these…

Numerical Analysis · Mathematics 2015-03-13 Michael Westdickenberg , Jon Wilkening

In this paper, we unify all know iterative methods by introducing a new explicit iterative scheme for approximation of common fixed points of finite families of total asymptotically $I$-nonexpansive mappings. Note that such a scheme…

Functional Analysis · Mathematics 2012-04-10 Farrukh Mukhamedov , Mansoor Saburov

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower…

Machine Learning · Statistics 2019-06-12 Nikolaos Gianniotis , Christoph Schnörr , Christian Molkenthin , Sanjay Singh Bora

We propose the symmetry reduction method of partial differential equations to the system of differential equations with fewer number of independent variables. We also obtain generalized sufficient conditions for the solution found by…

Mathematical Physics · Physics 2007-05-23 I. M. Tsyfra

A general method to generate a centrosymmetric matrix associated with the solving of partial differential equation (PDE) on an irreducible domain by means of a linear equation system is proposed. The method applies to any PDE for which both…

Numerical Analysis · Mathematics 2025-03-12 T. Thuillier

We study system design problems stated as parameterized stochastic programs with a chance-constraint set. We adopt a Bayesian approach that requires the computation of a posterior predictive integral which is usually intractable. In…

Machine Learning · Statistics 2020-01-07 Prateek Jaiswal , Harsha Honnappa , Vinayak A. Rao

A nonlinear equation in a Banach space is written as a linear equation with a linear operator depending on the unknown solution. This method, which we call a global linearization method, differs essentially from the local linearization…

Mathematical Physics · Physics 2007-05-23 A. G. Ramm

In multi-phase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise…

Numerical Analysis · Mathematics 2019-07-24 Chung-Nan Tzou , Samuel Stechmann

This work develops a class of probabilistic algorithms for the numerical solution of nonlinear, time-dependent partial differential equations (PDEs). Current state-of-the-art PDE solvers treat the space- and time-dimensions separately,…

Numerical Analysis · Mathematics 2022-03-10 Nicholas Krämer , Jonathan Schmidt , Philipp Hennig

In this work we study the existence of periodic and asymptotically periodic solutions of a system of nonlinear Volterra difference equations with infinite delay. By means of fixed point theory, we furnish conditions that guarantee the…

Classical Analysis and ODEs · Mathematics 2013-03-28 Murat Adıvar , H. Can Koyuncuoğlu , Youssef N. Raffoul

In this paper, using generalized metric projection, we propose a new extragradient method for finding a common element of the solutions set of a generalized equilibrium problem and a variational inequality for an $\alpha$-inverse-strongly…

Functional Analysis · Mathematics 2016-11-01 Zeynab Jouymandi , Fridoun Moradlou

An exponential time-integrator scheme of second-order accuracy based on the predictor-corrector methodology, denoted PCEXP, is developed to solve multi-dimensional nonlinear partial differential equations pertaining to fluid dynamics. The…

Computational Physics · Physics 2018-05-09 Shu-Jie Li , Li-Shi Luo , Z. J. Wang , Lili Ju

Mathematical models for flow and reactive transport in porous media often involve non-linear, degenerate parabolic equations. Their solutions have low regularity, and therefore lower order schemes are used for the numerical approximation.…

Numerical Analysis · Mathematics 2021-05-24 Jakub W. Both , Kundan Kumar , Jan M. Nordbotten , Iuliu Sorin Pop , Florin A. Radu

The branching methods developed are effective methods to solve some semi linear PDEs and are shown numerically to be able to solve some full non linear PDEs. These methods are however restricted to some small coefficients in the PDE and…

Probability · Mathematics 2017-01-27 Xavier Warin

In the present paper invariant subspace method has been extended for solving systems of multi-term fractional partial differential equations (FPDEs) involving both time and space fractional derivatives. Further the method has also been…

Analysis of PDEs · Mathematics 2019-04-02 Sangita Choudhary , Varsha Daftardar-Gejji

In this paper, we propose a multirate iterative scheme with multiphysics finite element method for a fluid-saturated poroelasticity model. Firstly, we reformulate the original model into a fluid coupled problem to apply the multiphysics…

Numerical Analysis · Mathematics 2021-09-28 Zhihao Ge , Xiangzi Fu

We consider the numerical approximation of compressible flow in a pipe network. Appropriate coupling conditions are formulated that allow us to derive a variational characterization of solutions and to prove global balance laws for the…

Numerical Analysis · Mathematics 2016-10-06 Herbert Egger

In this contribution we present the first formulation of a heterogeneous multiscale method for an incompressible immiscible two-phase flow system with degenerate permeabilities. The method is in a general formulation which includes…

Numerical Analysis · Mathematics 2014-11-24 Patrick Henning , Mario Ohlberger , Ben Schweizer

In this paper, we consider multipoint flux mixed finite element discretizations for slightly compressible Darcy flow in porous media. The methods are formulated on general meshes composed of triangles, quadrilaterals, tetrahedra or…

Numerical Analysis · Mathematics 2018-11-07 Andrés Arrarás , Laura Portero

There has been an arising trend of adopting deep learning methods to study partial differential equations (PDEs). In this paper, we introduce a deep recurrent framework for solving time-dependent PDEs without generating large scale data…

Numerical Analysis · Mathematics 2021-04-21 Cheng Chang , Liu Liu , Tieyong Zeng
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