A sequential sensor selection strategy for hyper-parameterized linear Bayesian inverse problems

Aretz-Nellesen, Nicole (Corresponding author)^RWTH* ; Chen, Peng (Corresponding author) ; Grepl, Martin A. (Corresponding author)^RWTH* ; Veroy-Grepl, Karen (Corresponding author)^RWTH*

2020

Umfang8 Seiten

Online
DOI: 10.48550/arXiv.2011.11391
10.48550/arXiv.2011.11391

Einrichtungen

Externer link:

Fulltext by arXiv.org

Dokumenttyp
Preprint

Format
online

Sprache
English

Externe Identnummern
arXiv: arXiv:2011.11391

Interne Identnummern
RWTH-2021-01500
Datensatz-ID: 811892

Beteiligte Länder
Germany, USA

Related:

Contribution to a book/Contribution to a conference proceedings Aretz-Nellesen, N.RWTH* ; Chen, P. ; Grepl, M. A. (Corresponding author)RWTH* ; Veroy-Grepl, K.RWTH*
A Sequential Sensor Selection Strategy for Hyper-Parameterized Linear Bayesian Inverse Problems
2021Numerical Mathematics and Advanced Applications ENUMATH 2019 European Conference, Egmond aan Zee, The Netherlands, September 30 - October 4
ENUMATH 2019 European Conference, ENUMATH 2019, Egmond aan ZeeEgmond aan Zee, Netherlands, 2021-09-30- 2021-10-042021-09-30- 2021-10-04 Cham : Springer International Publishing, Lecture notes in computational science and engineering book series 139, 489-497 (2021) [10.1007/978-3-030-55874-1_48]2021 BibTeX | EndNote: XML, Text | RIS