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Structural learning, a method to estimate the parameters for discrete energy minimization, has been proven to be effective in solving computer vision problems, especially in 3D scene parsing. As the complexity of the models increases,…

Computer Vision and Pattern Recognition · Computer Science 2017-01-13 Mengtian Li , Daniel Huber

We consider a scalar conservation law with linear and nonlinear flux function on a bounded domain $\Omega\subset{\R}^2$ with Lipschitz boundary $\partial\Omega.$ We discretize the spatial variable with the standard finite element method…

Numerical Analysis · Mathematics 2026-02-20 Christos Pervolianakis

One of main obstacles in verifying the energy dissipation laws of implicit-explicit Runge-Kutta (IERK) methods for phase field equations is to establish the uniform boundedness of stage solutions without the global Lipschitz continuity…

Numerical Analysis · Mathematics 2024-12-11 Hong-lin Liao , Tao Tang , Xuping Wang , Tao Zhou

This paper develops and analyzes an optimal-order semi-discrete scheme and its fully discrete finite element approximation for nonlinear stochastic elastic wave equations with multiplicative noise. A non-standard time-stepping scheme is…

Numerical Analysis · Mathematics 2025-04-08 Xiaobing Feng , Yukun Li , Liet Vo

This paper describes the recently developed mixed mimetic spectral element method for the Stokes problem in the vorticity-velocity-pressure formulation. This compatible discretization method relies on the construction of a conforming…

Numerical Analysis · Computer Science 2012-06-14 Jasper Kreeft , Marc Gerritsma

We present a hybrid a-priori/a-posteriori goal oriented error estimator for a combination of dynamic iteration-based solution of ordinary differential equations discretized by finite elements. Our novel error estimator combines estimates…

Numerical Analysis · Mathematics 2026-02-13 Erik Weyl , Andreas Bartel , Manuel Schaller

We consider an initial- and Dirichlet boundary- value problem for a fourth-order linear stochastic parabolic equation, in two or three space dimensions, forced by an additive space-time white noise. Discretizing the space-time white noise a…

Numerical Analysis · Mathematics 2009-06-11 Georgios T. Kossioris , Georgios E. Zouraris

The paper focuses on unconditionally optimal error analysis of the fully discrete Galerkin finite element methods for a general nonlinear parabolic system in $\R^d$ with $d=2,3$. In terms of a corresponding time-discrete system of PDEs as…

Numerical Analysis · Mathematics 2013-03-27 Buyang Li , Weiwei Sun

This paper is concerned with high moment and pathwise error estimates for both velocity and pressure approximations of the Euler-Maruyama scheme for time discretization and its two fully discrete mixed finite element discretizations. The…

Numerical Analysis · Mathematics 2021-07-01 Liet Vo

In this work we present an adaptive Newton-type method to solve nonlinear constrained optimization problems in which the constraint is a system of partial differential equations discretized by the finite element method. The adaptive…

Optimization and Control · Mathematics 2017-06-05 Thomas Carraro , Simon Dörsam , Stefan Frei , Daniel Schwarz

We derive a posteriori error estimates in the $L_\infty((0,T];L_\infty(\Omega))$ norm for approximations of solutions to linear para bolic equations. Using the elliptic reconstruction technique introduced by Makridakis and Nochetto and heat…

Numerical Analysis · Mathematics 2011-04-06 Alan Demlow , Omar Lakkis , Charalambos Makridakis

We use the local orthogonal decomposition technique to derive a generalized finite element method for linear and semilinear parabolic equations with spatial multiscale diffusion coefficient. We consider nonsmooth initial data and a backward…

Numerical Analysis · Mathematics 2015-05-01 Axel Målqvist , Anna Persson

This paper is concerned with the adaptive numerical treatment of stochastic partial differential equations. Our method of choice is Rothe's method. We use the implicit Euler scheme for the time discretization. Consequently, in each step, an…

In this work we consider the two dimensional instationary Navier-Stokes equations with homogeneous Dirichlet/no-slip boundary conditions. We show error estimates for the fully discrete problem, where a discontinuous Galerkin method in time…

Numerical Analysis · Mathematics 2026-05-20 Boris Vexler , Jakob Wagner

It is shown that for a parabolic problem with maximal $L^p$-regularity (for $1<p<\infty$), the time discretization by a linear multistep method or Runge--Kutta method has maximal $\ell^p$-regularity uniformly in the stepsize if the method…

Numerical Analysis · Mathematics 2016-08-06 Balázs Kovács , Buyang Li , Christian Lubich

Maximal regularity is a fundamental concept in the theory of partial differential equations. In this paper, we establish a fully discrete version of maximal regularity for a parabolic equation. We derive various stability results in…

Numerical Analysis · Mathematics 2016-02-23 Tomoya Kemmochi , Norikazu Saito

In this paper, both semidiscrete and fully discrete finite element methods are analyzed for the penalized two-dimensional unsteady Navier-Stokes equations with nonsmooth initial data. First order backward Euler method is applied for the…

Numerical Analysis · Mathematics 2026-04-16 Bikram Bir , Deepjyoti Goswami , Amiya K. Pani

We study finite element approximations of second-order elliptic problems with measure-valued right-hand sides supported on lower-dimensional sets. The exact solution generally lacks $H^1$-regularity due to the source singularity, which…

Numerical Analysis · Mathematics 2026-03-10 Huadong Gao , Yuhui Huang

Convergence results for the immersed boundary method applied to a model Stokes problem with the homogeneous Dirichlet boundary condition are presented. As a discretization method, we deal with the finite element method. First, the immersed…

Numerical Analysis · Mathematics 2020-01-24 Norikazu Saito , Yoshiki Sugitani

A focus of recent research in quantum computing has been on developing quantum algorithms for differential equations solving using variational methods on near-term quantum devices. A promising approach involves variational algorithms, which…

Quantum Physics · Physics 2026-02-03 David Dechant , Liubov Markovich , Vedran Dunjko , Jordi Tura