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We present an a posteriori error analysis for the mixed virtual element method (mixed VEM) applied to second order elliptic equations in divergence form with mixed boundary conditions. The resulting error estimator is of residual-type. It…

Numerical Analysis · Mathematics 2019-04-24 Andrea Cangiani , Mauricio Munar

We study Bayesian inverse problems with mixed noise, modeled as a combination of additive and multiplicative Gaussian components. While traditional inference methods often assume fixed or known noise characteristics, real-world…

Machine Learning · Computer Science 2025-10-17 Paul Hagemann , Robert Gruhlke , Bernhard Stankewitz , Claudia Schillings , Gabriele Steidl

Unconditionally stable finite element methods for Darcy flow are derived by adding least-squares residual forms of the governing equations to the classical mixed formulations. The proposed methods are free of mesh dependent stabilization…

Numerical Analysis · Mathematics 2025-05-27 Maicon R. Correa , Abimael F. D. Loula

We present a general framework for Bayesian estimation of incompletely observed multivariate diffusion processes. Observations are assumed to be discrete in time, noisy and incomplete. We assume the drift and diffusion coefficient depend on…

Methodology · Statistics 2019-02-04 Frank van der Meulen , Moritz Schauer

In this paper, we study the unconditional convergence and error estimates of a Galerkin-mixed FEM with the linearized semi-implicit Euler time-discrete scheme for the equations of incompressible miscible flow in porous media. We prove that…

Numerical Analysis · Mathematics 2013-10-01 Buyang Li , Weiwei Sun

We consider nonparametric estimation of a mixed discrete-continuous distribution under anisotropic smoothness conditions and possibly increasing number of support points for the discrete part of the distribution. For these settings, we…

Statistics Theory · Mathematics 2018-06-21 Andriy Norets , Justinas Pelenis

Hierarchical learning models, such as mixture models and Bayesian networks, are widely employed for unsupervised learning tasks, such as clustering analysis. They consist of observable and hidden variables, which represent the given data…

Machine Learning · Statistics 2018-01-08 Keisuke Yamazaki

Applied problems of oil and gas recovery are studied numerically using the mathematical models of multiphase fluid flows in porous media. The basic model includes the continuity equations and the Darcy laws for each phase, as well as the…

Numerical Analysis · Computer Science 2011-07-28 P. Vabishchevich , M. Vasil'eva

While many methods exist to discretize nonlinear time-dependent partial differential equations (PDEs), the rigorous estimation and adaptive control of their discretization errors remains challenging. In this paper, we present a methodology…

Numerical Analysis · Mathematics 2017-06-15 Xunxun Wu , Kristoffer van der Zee , Gorkem Simsek , Harald Van Brummelen

There is wide agreement that the accuracy of turbulence models suffer from their sensitivity with respect to physical input data, the uncertainties of user-elected parameters, as well as the model inadequacy. However, the application of…

Numerical Analysis · Mathematics 2015-08-07 Hoang A. Tran , Clayton G. Webster , Guannan Zhang

This paper develops a posteriori error estimates of residual type for conforming and mixed finite element approximations of the fourth order Cahn-Hilliard equation $u_t+\De\bigl(\eps \De u-\eps^{-1} f(u)\bigr)=0$. It is shown that the {\it…

Numerical Analysis · Mathematics 2007-08-17 Xiaobing Feng , Haijun Wu

Residual-based a~posteriori error estimators are derived for the modified Morley FEM, proposed by Wang, Xu, Hu [J. Comput. Math, 24(2), 2006], for the singularly perturbed biharmonic equation and the nonlinear von K\'arm\'an equations. The…

Numerical Analysis · Mathematics 2026-02-17 A. K. Dond , D. Gallistl , S. Nayak , M. Schedensack

There are very few results on mixed finite element methods on surfaces. A theory for the study of such methods was given recently by Holst and Stern, using a variational crimes framework in the context of finite element exterior calculus.…

Numerical Analysis · Computer Science 2011-03-28 Anil N. Hirani , Kaushik Kalyanaraman

This paper derives a posteriori error estimators for the nonlinear first-order optimality conditions associated with the Frank-Oseen elastic free-energy model of nematic and cholesteric liquid crystals, where the required unit-length…

Numerical Analysis · Mathematics 2017-09-20 D. B. Emerson

We introduce and explain key relations between a posteriori error estimates and subspace correction methods viewed as preconditioners for problems in infinite dimensional Hilbert spaces. We set the stage using the Finite Element Exterior…

Numerical Analysis · Mathematics 2025-04-16 Yuwen Li , Ludmil T. Zikatanov

An adaptive algorithm, based on residual type a posteriori indicators of errors measured in $L^{\infty}(L^2)$ and $L^2(L^2)$ norms, for a numerical scheme consisting of implicit Euler method in time and discontinuous Galerkin method in…

Numerical Analysis · Mathematics 2013-03-12 Emmanuil H. Georgoulis , Juha M. Virtanen

A posteriori estimates for mixed finite element discretizations of the Navier-Stokes equations are derived. We show that the task of estimating the error in the evolutionary Navier-Stokes equations can be reduced to the estimation of the…

Numerical Analysis · Mathematics 2016-12-23 Javier de Frutos , Bosco García-Archilla , Julia Novo

For elliptic interface problems in two- and three-dimensions, this paper establishes a priori error estimates for Crouzeix-Raviart nonconforming, Raviart-Thomas mixed, and discontinuous Galerkin finite element approximations. These…

Numerical Analysis · Mathematics 2015-10-26 Zhiqiang Cai , Shun Zhang

This paper derives a posteriori error estimates for the mixed numerical approximation of the Laplace eigenvalue problem with homogeneous Dirichlet boundary conditions. In particular, the resulting error estimator constitutes an upper bound…

Numerical Analysis · Mathematics 2021-01-26 Fleurianne Bertrand , Daniele Boffi , Rolf Stenberg

Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative methodology. In this paper, we make such networks estimate…

Computer Vision and Pattern Recognition · Computer Science 2018-12-21 Eddy Ilg , Özgün Çiçek , Silvio Galesso , Aaron Klein , Osama Makansi , Frank Hutter , Thomas Brox