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In this note, we extend the analysis for the residual-based a posteriori error estimators in the energy norm defined for the algebraic flux correction (AFC) schemes [Jha20.CAMWA] to the newly proposed algebraic stabilization schemes…

Numerical Analysis · Mathematics 2024-04-04 Abhinav Jha

This work is concerned with the derivation of a robust a posteriori error estimator for a discontinuous Galerkin method discretisation of linear non-stationary convection-diffusion initial/boundary value problems and with the implementation…

Numerical Analysis · Mathematics 2012-11-16 Andrea Cangiani , Emmanuil H. Georgoulis , Stephen Metcalfe

We consider the a posteriori error analysis of fully discrete approximations of parabolic problems based on conforming $hp$-finite element methods in space and an arbitrary order discontinuous Galerkin method in time. Using an equilibrated…

Numerical Analysis · Mathematics 2018-12-18 Alexandre Ern , Iain Smears , Martin Vohralik

Non-linear statistical inverse problems pose major challenges both for statistical analysis and computation. Likelihood-based estimators typically lead to non-convex and possibly multimodal optimization landscapes, and Markov chain Monte…

Statistics Theory · Mathematics 2026-01-15 Sven Wang

Nonparametric mixture models based on the Dirichlet process are an elegant alternative to finite models when the number of underlying components is unknown, but inference in such models can be slow. Existing attempts to parallelize…

Machine Learning · Statistics 2012-12-03 Sinead A. Williamson , Avinava Dubey , Eric P. Xing

In this work, we propose a residual-based a posteriori error estimator for algebraic flux-corrected (AFC) schemes for stationary convection-diffusion equations. A global upper bound is derived for the error in the energy norm for a general…

Numerical Analysis · Mathematics 2024-01-15 Abhinav Jha

In the present work, we derive functional upper bounds for the potential error arising from finite-element boundary-element coupling formulations for a nonlinear Poisson-type transmission problem. The proposed a posteriori error estimates…

Numerical Analysis · Mathematics 2026-02-17 Alexander Freiszlinger , Dirk Pauly , Dirk Praetorius , Michael Schomburg

The Richards equation is commonly used to model the flow of water and air through soil, and it serves as a gateway equation for multiphase flows through porous media. It is a nonlinear advection-reaction-diffusion equation that exhibits…

Numerical Analysis · Mathematics 2021-08-31 K. Mitra , M. Vohralík

In this paper we develop an a posteriori error analysis for the stationary Stokes-Darcy coupled problem approximated by conforming finite element method on isotropic meshes in $\mathbb{R}^d$, $d\in\{2,3\}$. The approach utilizes a new…

Numerical Analysis · Mathematics 2020-04-10 Koffi Wilfrid Houédanou , Jamal Adetola

Although the numerical results suggest the optimal convergence order of the two-grid finite element decoupled scheme for mixed Stokes-Darcy model with Beaver-Joseph-Saffman interface condition in literatures, the numerical analysis only get…

Numerical Analysis · Mathematics 2016-02-08 Yanren Hou

In a general setting, we study a posteriori estimates used in finite element analysis to measure the error between a solution and its approximation. The latter is not necessarily generated by a finite element method. We show that the error…

Numerical Analysis · Mathematics 2025-07-09 Thomas Führer , Sergio Rojas

We consider three-dimensional convection of an incompressible fluid saturated in a parallelepiped with a porous medium. A mimetic finite-difference scheme for the Darcy convection problem in the primitive variables is developed. It consists…

Chaotic Dynamics · Physics 2009-11-13 B. Karasozen , A. D. Nemtsev , V. G. Tsybulin

We propose an a posteriori error estimator for a sparse optimal control problem: the control variable lies in the space of regular Borel measures. We consider a solution technique that relies on the discretization of the control variable as…

Numerical Analysis · Mathematics 2018-06-14 Francisco Fuica , Enrique Otarola , Abner J. Salgado

This article describes the extension of recent methods for a posteriori error estimation such as dual-weighted residual methods to node-centered finite volume discretizations of second order elliptic boundary value problems including upwind…

Numerical Analysis · Mathematics 2026-02-04 Lutz Angermann

We design and analyze multigrid methods for the saddle point problems resulting from Raviart-Thomas-N\'ed\'elec mixed finite element methods (of order at least 1) for the Darcy system in porous media flow. Uniform convergence of the…

Numerical Analysis · Mathematics 2015-11-30 Susanne C. Brenner , Duk-Soon Oh , Li-yeng Sung

A computational method based on the non-linear Gaussian process (GP), known as deep Gaussian processes (deep GPs) for uncertainty quantification & propagation in modelling of flow through heterogeneous porous media is presented. The method…

Machine Learning · Statistics 2020-11-06 A. Daneshkhah , O. Chatrabgoun , M. Esmaeilbeigi , T. Sedighi , S. Abolfathi

We derive a residual based a-posteriori error estimate for the outer normal flux of approximations to {the diffusion problem with variable coefficient}. By analyzing the solution of the adjoint problem, we show that error indicators in the…

Numerical Analysis · Mathematics 2021-10-26 Silvia Bertoluzza , Erik Burman , Cuiyu He

The pressure and flow statistics of Darcy flow through a random permeable medium are expressed in a form suitable for evaluation by the method of simulated annealing. There are several attractive aspects to using simulated annealing: (i)…

Computational Engineering, Finance, and Science · Computer Science 2019-04-04 Marise J. E. Westbroek , Peter R. King , Dimitri D. Vvedensky , Ronnie L. Schwede

We present a novel technique for amortized posterior estimation using Normalizing Flows trained with likelihood-weighted importance sampling. This approach allows for the efficient inference of theoretical parameters in high-dimensional…

Machine Learning · Computer Science 2026-02-23 Rajneil Baruah

This work presents mixed variational flows (MixFlows), a new variational family that consists of a mixture of repeated applications of a map to an initial reference distribution. First, we provide efficient algorithms for i.i.d. sampling,…

Machine Learning · Statistics 2025-06-03 Zuheng Xu , Naitong Chen , Trevor Campbell