174 research outputs found
Replication Data for: Learned infinite elements
No full textThis dataset contains reproduction material for the paper "Learned infinite elements" (Hohage, Lehrenfeld, Preuss).
The main file learnedIE_reproduction.tar is a Docker image providing all data, software and instructions for reproducing the numerical experiments of the paper.
This image was built based on the Github repository github.com/schruste/docker-learned_IE . The main repository containing the actual software and data is gitlab.gwdg.de/learned_infinite_elements/learned_ie/ at commit ed8d1d9f1a7fe1daea11a5323ea831eb34a17924. The tarball learned_ie_git-repo.tar.gz contains an archive of this repository. A README file is included in the repository as well as in learnedIE_reproduction.tar, which contains detailed instructions (which commands to execute and so on) on how to obtain the results given in the paper.
The image can additionally be found on Docker Hub: schruste/learned_ie:2021051
An iterative method for inverse medium scattering problems based on factorization of the far field operator
No full textFast numerical solution of the electromagnetic medium scattering problem and applications to the inverse problem
No full textConvergence Rates of a Regularized Newton Method in Sound-Hard Inverse Scattering
No full textThe iteratively regularized Gauss--Newton method is used to solve an inverse acoustic scattering problem with Neumann boundary conditions in two space dimensions, which is known to be nonlinear and severely ill posed. Some recent results on the speed of convergence for such problems are considered, and numerical experiments yield logarithmic convergence rates, as expected. Moreover, we present an efficient method to numerically evaluate the Fréchet derivative using its characterization as a boundary value problem and prove fast convergence of this method. Read More: https://epubs.siam.org/doi/10.1137/S003614299732775
Iterative Methods in Inverse Obstacle Scattering: Regularization Theory of Linear and Nonlinear Exponentially ill-posed Problems
No full textRegularization of Exponentially ill-posed Problems
No full textLinear and nonlinear inverse problems which are exponentially ill-posed arise in heat conduction, satellite gradiometry, potential theory and scattering theory. For these problems logarithmic source conditions have natural interpretations whereas standard Hölder-type source conditions are far too restrictive. This paper provides a systematic study of convergence rates of regularization methods under logarithmic source conditions including the case that the operator is given onlyapproximately. We also extend previous convergence results for the iteratively regularized Gauß-Newton method to operator approximations
Logarithmic Convergence Rates of the iteratively regularized Gauss-Newton method for an inverse potential and an inverse scattering problem
No full textConvergence rates in expectation for Tikhonov-type regularization of Inverse Problems with Poisson data
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