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Related papers: A-posteriori error estimates for inverse problems

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In this paper, we study two residual-based a posteriori error estimators for the $C^0$ interior penalty method in solving the biharmonic equation in a polygonal domain under a concentrated load. The first estimator is derived directly from…

Numerical Analysis · Mathematics 2024-08-29 Huihui Cao , Yunqing Huang , Nianyu Yi , Peimeng Yin

The binary Mumford-Shah model is a widespread tool for image segmentation and can be considered as a basic model in shape optimization with a broad range of applications in computer vision, ranging from basic segmentation and labeling to…

Numerical Analysis · Mathematics 2015-05-21 Benjamin Berkels , Alexander Effland , Martin Rumpf

In this work we derive a posteriori error estimates for the convection-diffusion-reaction equation coupled with the Darcy-Forchheimer problem by a nonlinear external source depending on the concentration of the fluid. We introduce the…

Numerical Analysis · Mathematics 2022-12-27 Toni Sayah , Georges Semaan , Faouzi Triki

In this paper, the a posteriori error estimates of the exponential midpoint method for time discretization are studied for linear and semilinear parabolic equations. Using the exponential midpoint approximation defined by a continuous and…

Numerical Analysis · Mathematics 2024-06-13 Xianfa Hu , Wansheng Wang , Mengli Mao , Jiliang Cao

Probabilistic solvers for ordinary differential equations assign a posterior measure to the solution of an initial value problem. The joint covariance of this distribution provides an estimate of the (global) approximation error. The…

Numerical Analysis · Mathematics 2021-02-23 Nathanael Bosch , Philipp Hennig , Filip Tronarp

In this paper, we consider an inverse problem to determine a source term in a parabolic equation, where the data are obtained at a certain time. In general, this problem is ill-posed, therefore the Tikhonov regularization method is proposed…

Analysis of PDEs · Mathematics 2015-12-10 Nguyen Huy Tuan , Nguyen Van Thinh , Vo Anh Khoa , Tran Thanh Binh

We present a computational framework for estimating the uncertainty in the numerical solution of linearized infinite-dimensional statistical inverse problems. We adopt the Bayesian inference formulation: given observational data and their…

Numerical Analysis · Mathematics 2013-08-07 Tan Bui-Thanh , Omar Ghattas , James Martin , Georg Stadler

This paper develops a methodology for approximating the posterior first two moments of the posterior distribution in Bayesian inference. Partially specified probability models, which are defined only by specifying means and variances, are…

Methodology · Statistics 2009-01-27 K. Triantafyllopoulos , P. J. Harrison

We derive a residual-based $hp$-a posteriori error estimator for hybrid high-order (HHO) methods on simplicial meshes applied to the biharmonic problem posed on two- and three-dimensional polytopal Lipschitz domains. The a posteriori error…

Numerical Analysis · Mathematics 2026-02-09 Zhaonan Dong , Alexandre Ern , Tanvi Wadhawan

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

In this article, goal-oriented a posteriori error estimation for the biharmonic plate bending problem is considered. The error for approximation of goal functional is represented by an estimator which combines dual-weighted residual method…

Numerical Analysis · Mathematics 2021-07-15 Gouranga Mallik

In this work, we propose an a pointwise a posteriori error estimator for conforming finite element approximations of eigenfunctions corresponding to multiple and clustered eigenvalues of elliptic operators. It is proven that the pointwise a…

Numerical Analysis · Mathematics 2025-11-12 Zhenglei Li , Qigang Liang , Xuejun Xu

The inverse problem is studied in multi-body systems with nonlinear dynamics representing, e.g., phase-locked wave systems, standard multimode and random lasers. Using a general model for four-body interacting complex-valued variables we…

Disordered Systems and Neural Networks · Physics 2017-08-01 Alessia Marruzzo , Payal Tyagi , Fabrizio Antenucci , Andrea Pagnani , Luca Leuzzi

Machine learning methods for computational imaging require uncertainty estimation to be reliable in real settings. While Bayesian models offer a computationally tractable way of recovering uncertainty, they need large data volumes to be…

Machine Learning · Computer Science 2020-08-24 Francesco Tonolini , Jack Radford , Alex Turpin , Daniele Faccio , Roderick Murray-Smith

The inverse problem methodology is a commonly-used framework in the sciences for parameter estimation and inference. It is typically performed by fitting a mathematical model to noisy experimental data. There are two significant sources of…

Numerical Analysis · Mathematics 2018-07-26 John T. Nardini , D. M. Bortz

This work develops polynomial-degree-robust (p-robust) equilibrated a posteriori error estimates for $H(\rm curl)$, $H(\rm div)$ and $H(\rm divdiv)$ problems, based on $H^1$ auxiliary space decomposition. The proposed framework employs…

Numerical Analysis · Mathematics 2025-11-14 Yuwen Li

In this article, a posteriori error analysis of the elliptic obstacle problem is addressed using hybrid high-order methods. The method involve cell unknowns represented by degree-$r$ polynomials and face unknowns represented by degree-$s$…

Numerical Analysis · Mathematics 2024-05-09 Kamana Porwal , Ritesh Singla

A general a posteriori error analysis applies to five lowest-order finite element methods for two fourth-order semi-linear problems with trilinear non-linearity and a general source. A quasi-optimal smoother extends the source term to the…

Numerical Analysis · Mathematics 2023-09-18 Carsten Carstensen , Benedikt Gräßle , Neela Nataraj

The Bayesian approach has proved to be a coherent approach to handle ill posed Inverse problems. However, the Bayesian calculations need either an optimization or an integral calculation. The maximum a posteriori (MAP) estimation requires…

Data Analysis, Statistics and Probability · Physics 2007-05-23 A. Mohammad-Djafari

We consider a mixed variational formulation recently proposed for the coupling of the Brinkman--Forchheimer and Darcy equations and develop the first reliable and efficient residual-based a posteriori error estimator for the 2D version of…

Numerical Analysis · Mathematics 2024-12-02 Sergio Caucao , Paulo Zúñiga
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