Results 201 to 210 of about 35,012 (233)

Variational State-Dependent Inverse Problems in PDE-Constrained Optimization: A Survey of Contemporary Computational Methods and Applications [PDF]

Vladislav Bukshtynov
openalex  

On local constraints and regularity of PDE in electromagnetics. Applications to hybrid imaging inverse problems

, 2014
Giovanni S. Alberti
openalex   +1 more source

Solving Inverse PDE Problems using Minimization Methods and AI [PDF]

Noura Al Helwani, Sophie Moufawad, Georges Sakr   +2 more
openalex  

Correction to: Remarks on control and inverse problems for PDEs

SeMA Journal
openaire   +1 more source

Goal-oriented optimal sensor placement for PDE-constrained inverse problems

Mattuschka, Marco, von Danwitz, Max, Popp, Alexander   +2 more
openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Stochastic Algorithms for Inverse Problems Involving PDEs and many Measurements

SIAM Journal on Scientific Computing, 2014
Inverse problems involving systems of partial differential equations (PDEs) can be very expensive to solve numerically. This is so especially when many experiments, involving different combinations of sources and receivers, are employed in order to obtain reconstructions of acceptable quality.
Roosta-Khorasani, Farbod, Van Den Doel, Kees, Ascher, Uri   +2 more
openaire   +4 more sources

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

SIAM Journal on Scientific Computing, 2022
This paper deals with solving an inverse problem of electrocardiography involving deep learning (DL). In more detail: ``The goal of this work is to show how the integration between DL techniques and physically based regularization allows one to accurately solve the inverse problem of electrocardiography, even in a small data regime.'' (page B608).
Riccardo Tenderini, Stefano Pagani, Alfio Quarteroni, Simone Deparis   +3 more
openaire   +2 more sources

Numerical Solution Of Inverse Problem For Elliptic Pdes

International Journal of Computer Mathematics, 2003
This work is concerned with computing the solution of the following inverse problem: Finding u and „on D such that: $$\nabla \cdot (\rho \nabla u) = 0,\quad \hbox{on}\ D;$$ $$u = g,\quad \hbox{on}\ \partial D;\qquad \rho u_n = f,\quad \hbox{on}\ \partial D;$$ $$\rho (x_0, y_0) = \rho_0,\quad \hbox{for a given point}\ (x_0, y_0) \in D$$ where f and g ...
Ali Sayfy, Sadia Makky
openaire   +1 more source

Deep Learning for PDE-based Inverse Problems

Oberwolfach Reports
Workshop ...
Simon Arridge, Peter Maaß, Carola-Bibiane Schönlieb   +2 more
openaire   +2 more sources

A probabilistic white‐box model for PDE constrained inverse problems

PAMM, 2018
AbstractInstead of employing deterministic solvers in a black‐box fashion, we seek to address the inherent challenges of uncertainty quantification by restating the solution of a PDE as a problem of probabilistic inference. In doing so, state variables are treated as random fields, constrained or mutually entangled by underlying physical laws.
Maximilian Koschade, Phaedon‐Stelios Koutsourelakis   +1 more
openaire   +1 more source