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This paper develops a probabilistic numerical method for solution of partial differential equations (PDEs) and studies application of that method to PDE-constrained inverse problems. This approach enables the solution of challenging inverse…

Methodology · Statistics 2017-07-12 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami

Verification of solutions is crucial for establishing the reliability of simulations. A central challenge is to find an accurate and reliable estimate of the discretization error. Current approaches to this estimation rely on the observed…

Numerical Analysis · Mathematics 2023-01-18 Sharp Chim Yui Lo

This paper is concerned with adaptive mesh refinement strategies for the spatial discretization of parabolic problems with dynamic boundary conditions. This includes the characterization of inf-sup stable discretization schemes for a…

Numerical Analysis · Mathematics 2023-10-12 Robert Altmann , Christoph Zimmer

In this paper, we introduce a technique to enhance the computational efficiency of solution algorithms for high-dimensional discrete simulation-based optimization problems. The technique is based on innovative adaptive partitioning…

Optimization and Control · Mathematics 2024-12-04 Jing Lu , Tianli Zhou , Carolina Osorio

We propose a new paradigm for designing efficient p-adaptive arbitrary high order methods. We consider arbitrary high order iterative schemes that gain one order of accuracy at each iteration and we modify them in order to match the…

Numerical Analysis · Mathematics 2023-11-09 Lorenzo Micalizzi , Davide Torlo , Walter Boscheri

In this paper, we derive a practical, general framework for creating adaptive iterative (linearization or splitting) algorithms to solve multi-physics problems. This means that, given an iterative method, we derive \textit{a posteriori}…

Numerical Analysis · Mathematics 2026-01-26 Jakob S. Stokke , Kundan Kumar , Florin A. Radu

Discrete optimization problems often arise in deep learning tasks, despite the fact that neural networks typically operate on continuous data. One class of these problems involve objective functions which depend on neural networks, but…

Machine Learning · Computer Science 2023-10-17 Eric Lei , Arman Adibi , Hamed Hassani

This article aims to demonstrate and discuss the applications of automatic differentiation (AD) for finding derivatives in PDE-constrained optimization problems and Jacobians in non-linear finite element analysis. The main idea is to…

Numerical Analysis · Mathematics 2025-06-03 Julian Andrej , Tzanio Kolev , Boyan Lazarov

This paper presents an a-posteriori goal-oriented error analysis for a numerical approximation of the steady Boltzmann equation based on a moment-system approximation in velocity dependence and a discontinuous Galerkin finite-element (DGFE)…

Numerical Analysis · Mathematics 2017-10-11 M. R. A. Abdelmalik , E. H. van Brummelen

Strong approximation errors of both finite element semi-discretization and spatio-temporal full discretization are analyzed for the stochastic Allen-Cahn equation driven by additive noise in space dimension $d \leq 3$. The full…

Numerical Analysis · Mathematics 2020-08-04 Ruisheng Qi , Xiaojie Wang

We present a residual-based a posteriori error estimator for the hybrid high-order (HHO) method for the Stokes model problem. Both the proposed HHO method and error estimator are valid in two and three dimensions and support arbitrary…

Numerical Analysis · Mathematics 2021-03-26 Yongchao Zhang , Liquan Mei , Gang Wang

A discretization scheme for variable coefficient elliptic PDEs in the plane is presented. The scheme is based on high-order Gaussian quadratures and is designed for problems with smooth solutions, such as scattering problems involving soft…

Numerical Analysis · Mathematics 2015-03-17 Per-Gunnar Martinsson

Segmented models are widely used to describe non-stationary sequential data with discrete change points. Their estimation usually requires solving a mixed discrete-continuous optimization problem, where the segmentation is the discrete part…

Machine Learning · Computer Science 2021-01-19 Erik Scharwächter , Jonathan Lennartz , Emmanuel Müller

We consider second-order PDE problems set in unbounded domains and discretized by Lagrange finite elements on a finite mesh, thus introducing an artificial boundary in the discretization. Specifically, we consider the reaction diffusion…

Numerical Analysis · Mathematics 2025-03-31 T. Chaumont-Frelet

We present a novel approach for high-order accurate numerical differentiation on unstructured meshes of quadrilateral elements. To differentiate a given function, an auxiliary function with greater smoothness properties is defined which…

Numerical Analysis · Mathematics 2022-05-11 Yulong Pan , Per-Olof Persson

We consider an initial- and boundary- value problem for the nonlinear Schr\"odinger equation with homogeneous Dirichlet boundary conditions in the one space dimension case. We discretize the problem in space by a central finite difference…

Numerical Analysis · Mathematics 2020-02-25 Georgios E. Zouraris

We consider a linear-quadratic elliptic optimal control problem with point evaluations of the state variable in the cost functional. The state variable is discretized by conforming linear finite elements. For control discretization, three…

Numerical Analysis · Mathematics 2018-02-09 Niklas Behringer , Dominik Meidner , Boris Vexler

This paper builds on the algebraic theory in the companion paper [Algebraic Error Analysis for Mixed-Precision Multigrid Solvers] to obtain discretization-error-accurate solutions for linear elliptic partial differential equations (PDEs) by…

Numerical Analysis · Mathematics 2020-07-15 Rasmus Tamstorf , Joseph Benzaken , Stephen F. McCormick

We discuss goal-oriented adaptivity in the frame of conforming finite element methods and plain convergence of the related a posteriori error estimator for different general marking strategies. We present an abstract analysis for two…

Numerical Analysis · Mathematics 2024-07-30 Valentin Helml , Michael Innerberger , Dirk Praetorius

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical…

Numerical Analysis · Computer Science 2015-06-22 John D. Jakeman , Timothy Wildey