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The nonconforming virtual element method (NCVEM) for the approximation of the weak solution to a general linear second-order non-selfadjoint indefinite elliptic PDE in a polygonal domain is analyzed under reduced elliptic regularity. The…

Numerical Analysis · Mathematics 2022-03-15 Carsten Carstensen , Rekha Khot , Amiya K. Pani

In $L_2 (\mathbb{R}^d; \mathbb{C}^n)$, we consider a selfadjoint matrix strongly elliptic second order differential operator $\mathcal{A}_\varepsilon$ with periodic coefficients depending on $\mathbf{x}/\varepsilon$. We find approximations…

Analysis of PDEs · Mathematics 2019-05-14 Mark Dorodnyi

With this contribution, we shed light on the relation between the discrete adjoints of multistep backward differentiation formula (BDF) methods and the solution of the adjoint differential equation. To this end, we develop a…

Numerical Analysis · Mathematics 2011-09-15 Dörte Beigel , Mario S. Mommer , Leonard Wirsching , Hans Georg Bock

We derive functional a posteriori error equalities and constant free two sided estimates for certain types of partial differential equations. The error is measured in a combined norm which takes into account both the primal and dual…

Analysis of PDEs · Mathematics 2015-12-29 Immanuel Anjam , Dirk Pauly

We propose a time-space discretization scheme for quasi-linear parabolic PDEs. The algorithm relies on the theory of fully coupled forward--backward SDEs, which provides an efficient probabilistic representation of this type of equation.…

Probability · Mathematics 2016-08-16 François Delarue , Stéphane Menozzi

The numerical solution of partial differential equations (PDEs) is challenging because of the need to resolve spatiotemporal features over wide length and timescales. Often, it is computationally intractable to resolve the finest features…

Disordered Systems and Neural Networks · Physics 2019-08-22 Yohai Bar-Sinai , Stephan Hoyer , Jason Hickey , Michael P. Brenner

Variational Autoencoders and their many variants have displayed impressive ability to perform dimensionality reduction, often achieving state-of-the-art performance. Many current methods however, struggle to learn good representations in…

Machine Learning · Computer Science 2023-06-28 Navindu Leelarathna , Andrei Margeloiu , Mateja Jamnik , Nikola Simidjievski

The a posteriori error estimates are studied for a class of nonlinear stead-state Poisson-Nernst-Planck equations, which are a coupled system consisting of the Nernst-Planck equation and the Poisson equation. Both the global upper bounds…

Numerical Analysis · Mathematics 2020-01-10 Ying Yang , Ruigang Shen , Mingjuan Fang , Shi Shu

We extend the framework of a posteriori error estimation by preconditioning in [Li, Y., Zikatanov, L.: Computers \& Mathematics with Applications. \textbf{91}, 192-201 (2021)] and derive new a posteriori error estimates for H(curl)-elliptic…

Numerical Analysis · Mathematics 2023-04-06 Yuwen Li

In this paper we analyze a posteriori error estimates for a mixed formulation of the linear elasticity eigenvalue problem. A posteriori estimators for the nearly and perfectly compressible elasticity spectral problems are proposed. With a…

Numerical Analysis · Mathematics 2022-01-12 Felipe Lepe , Gonzalo Rivera , Jesús Vellojín

We consider several examples of nonautonomous systems of difference equations coming from semi-classical orthogonal polynomials via recurrence coefficients and ladder operators, with respect to various generalisations of Laguerre and…

Exactly Solvable and Integrable Systems · Physics 2026-04-16 Anton Dzhamay , Galina Filipuk , Alexander Stokes

In the theory and practice of inverse problems for partial differential equations (PDEs) much attention is paid to the problem of the identification of coefficients from some additional information. This work deals with the problem of…

Numerical Analysis · Computer Science 2013-04-23 P. N. Vabishchevich , V. I. Vasil'ev

In this paper we develop a new a posteriori error analysis for the Monge-Amp\`ere equation approximated by conforming finite element method on isotropic meshes in 2D. The approach utilizes a slight variant of the mixed discretization…

Numerical Analysis · Mathematics 2019-12-06 Jamal Adetola , Koffi Wilfrid Houedanou , Bernardin Ahounou

Differential equations (DEs) are commonly used to describe dynamic systems evolving in one (ordinary differential equations or ODEs) or in more than one dimensions (partial differential equations or PDEs). In real data applications the…

Methodology · Statistics 2013-11-25 Gianluca Frasso , Jonathan Jaeger , Philippe Lambert

We represent an algorithm allowing one to construct new classes of partially integrable multidimensional nonlinear partial differential equations (PDEs) starting with the special type of solutions to the (1+1)-dimensional hierarchy of…

Exactly Solvable and Integrable Systems · Physics 2015-05-13 A. I. Zenchuk

We consider the numerical approximation of general semilinear parabolic stochastic partial differential equations (SPDEs) driven by additive space-time noise. In contrast to the standard time stepping methods which uses basic increments of…

Numerical Analysis · Mathematics 2010-05-31 Gabriel J. Lord , Antoine Tambue

Parameter identification problems in partial differential equations (PDEs) consist in determining one or more functional coefficient in a PDE. In this article, the Bayesian nonparametric approach to such problems is considered. Focusing on…

Statistics Theory · Mathematics 2025-04-24 Matteo Giordano

A posteriori error estimates are constructed for the three-field variational formulation of the Biot problem involving the displacements, the total pressure and the fluid pressure. The discretization under focus is the…

Numerical Analysis · Mathematics 2020-11-19 F. Bertrand , G. Starke

In this paper, we develop an ensemble-based time-stepping algorithm to efficiently find numerical solutions to a group of linear, second-order parabolic partial differential equations (PDEs). Particularly, the PDE models in the group could…

Numerical Analysis · Mathematics 2017-10-18 Yan Luo , Zhu Wang

Given a partial differential equation (PDE), goal-oriented error estimation allows us to understand how errors in a diagnostic quantity of interest (QoI), or goal, occur and accumulate in a numerical approximation, for example using the…

Machine Learning · Computer Science 2022-07-25 Joseph G. Wallwork , Jingyi Lu , Mingrui Zhang , Matthew D. Piggott
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