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In this paper, we develop a class of interacting particle Langevin algorithms to solve inverse problems for partial differential equations (PDEs). In particular, we leverage the statistical finite elements (statFEM) formulation to obtain a…

Fourier solvers have become efficient tools to establish structure-property relations in heterogeneous materials. Introduced as an alternative to the Finite Element (FE) method, they are based on fixed-point solutions of the…

Computational Physics · Physics 2017-09-01 Jan Zeman , Tom W. J. de Geus , Jaroslav Vondřejc , Ron H. J. Peerlings , Marc G. D. Geers

Quantitative characterization of tissue properties, known as elasticity imaging, can be cast as solving an ill-posed inverse problem. The finite element methods (FEMs) in magnetic resonance elastography (MRE) imaging are based on solving a…

Image and Video Processing · Electrical Eng. & Systems 2021-03-29 Narges Mohammadi , Marvin M. Doyley , Mujdat Cetin

In this paper, we develop a gradient recovery based linear (GRBL) finite element method (FEM) and a Hessian recovery based linear (HRBL) FEM for second order elliptic equations in non-divergence form. The elliptic equation is casted into a…

Numerical Analysis · Mathematics 2022-11-09 Minqiang Xu , Runchang Lin , Qingsong Zou

We develop a geometrically intrinsic formulation of the arbitrary-order Virtual Element Method (VEM) on polygonal cells for the numerical solution of elliptic surface partial differential equations (PDEs). The PDE is first written in…

Numerical Analysis · Mathematics 2021-05-07 Elena Bachini , Gianmarco Manzini , Mario Putti

Infinite-dimensional Newton methods can be effectively used to derive numerical proofs of the existence of solutions to partial differential equations (PDEs). In computer-assisted proofs of PDEs, the original problem is transformed into the…

Numerical Analysis · Mathematics 2020-10-27 Kouta Sekine , Mitsuhiro T. Nakao , Shin'ichi Oishi

In this article I present a fast and direct method for solving several types of linear finite difference equations (FDE) with constant coefficients. The method is based on a polynomial form of the translation operator and its inverse, and…

Numerical Analysis · Mathematics 2011-11-03 S. Merino

The objective of electrical impedance tomography is to deduce information about the conductivity inside a physical body from electrode measurements of current and voltage at the object boundary. In this work, the unknown conductivity is…

Numerical Analysis · Mathematics 2015-04-28 Nuutti Hyvönen , Matti Leinonen

Hybrid inverse problems such as Acousto-Electric Tomography, Current Density Imaging or Magnetic Resonance Electric Impedance Tomography are concerned with reconstructing the electrical conductivity from interior measurements. For a…

Analysis of PDEs · Mathematics 2024-11-12 Hjørdis Schlüter

We design an adaptive finite element method to approximate the solutions of quasi-linear elliptic problems. The algorithm is based on a Ka\v{c}anov iteration and a mesh adaptation step is performed after each linear solve. The method is…

Numerical Analysis · Mathematics 2010-06-18 Eduardo M. Garau , Pedro Morin , Carlos Zuppa

We formulate and analyze a goal-oriented adaptive finite element method (GOAFEM) for a semilinear elliptic PDE and a linear goal functional. The strategy involves the finite element solution of a linearized dual problem, where the…

Numerical Analysis · Mathematics 2022-09-27 Roland Becker , Maximilian Brunner , Michael Innerberger , Jens Markus Melenk , Dirk Praetorius

We investigate the iterative methods proposed by Maz'ya and Kozlov (see [KM1], [KM2]) for solving ill-posed inverse problems modeled by partial differential equations. We consider linear evolutionary problems of elliptic, hyperbolic and…

Numerical Analysis · Mathematics 2020-12-01 J. Baumeister , A. Leitao

We propose a neural network-based algorithm for solving forward and inverse problems for partial differential equations in unsupervised fashion. The solution is approximated by a deep neural network which is the minimizer of a cost…

Machine Learning · Computer Science 2019-04-12 Leah Bar , Nir Sochen

We derive computable error estimates for finite element approximations of linear elliptic partial differential equations (PDE) with rough stochastic coefficients. In this setting, the exact solutions contain high frequency content that…

Numerical Analysis · Mathematics 2018-09-18 Eric Joseph Hall , Håkon Hoel , Mattias Sandberg , Anders Szepessy , Raúl Tempone

We present a methodology combining neural networks with physical principle constraints in the form of partial differential equations (PDEs). The approach allows to train neural networks while respecting the PDEs as a strong constraint in…

Numerical Analysis · Mathematics 2021-09-06 Sebastian K. Mitusch , Simon W. Funke , Miroslav Kuchta

In multi-phase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise…

Numerical Analysis · Mathematics 2019-07-24 Chung-Nan Tzou , Samuel Stechmann

A convexification-based numerical method for a Coefficient Inverse Problem for a parabolic PDE is presented. The key element of this method is the presence of the so-called Carleman Weight Function in the numerical scheme. Convergence…

Numerical Analysis · Mathematics 2020-01-10 Michael V. Klibanov , Jingzhi Li , Wenlong Zhang

In this work, we numerically investigate the inverse Robin problem of recovering a piecewise constant Robin coefficient in an elliptic or parabolic problem from the Cauchy data on a part of the boundary, a problem that commonly arises in…

Numerical Analysis · Mathematics 2025-06-10 Erik Burman , Siyu Cen , Bangti Jin , Zhi Zhou

This paper is concerned with the forward and inverse problems for the fractional semilinear elliptic equation $(-\Delta)^s u +a(x,u)=0$ for $0<s<1$. For the forward problem, we proved the problem is well-posed and has a unique solution for…

Analysis of PDEs · Mathematics 2020-04-02 Ru-Yu Lai , Yi-Hsuan Lin

We consider a compressed sensing problem in which both the measurement and the sparsifying systems are assumed to be frames (not necessarily tight) of the underlying Hilbert space of signals, which may be finite or infinite dimensional. The…

Information Theory · Computer Science 2020-10-15 Giovanni S. Alberti , Matteo Santacesaria