Ghent University Academic Bibliography

Advanced

Polynomial chaos forward models in Bayesian inference to solve inverse problems

Rob De Staelen UGent, Roger Van Keer, Karim Beddek, Stéphane Clenet and Olivier Moreau (2011) JSAEM Studies in Applied Electromagnetics and Mechanics. 14. p.525-526
abstract
In this paper we introduce polynomial chaos in the stochastic forward model used to solve the inverse problem through Bayesian inference. We validate our approach with three different methods that construct the stochastic forward model, to treat the TEAM Workshop Problem 8.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
in
JSAEM Studies in Applied Electromagnetics and Mechanics
JSAEM Stud. Appl. Electromagn. Mech.
editor
G Rubinacci, A Tamburrino, F Villone and T Takagi
volume
14
issue title
Proceedings of the 15th international symposium on applied electromagnetics and mechanics
pages
525 - 526
publisher
IOS Press
conference name
15th International symposium on Applied Electromagnetics and Mechanics
conference location
Napoli, Italy
conference start
2011-09-07
conference end
2011-09-09
ISSN
1343-2869
ISBN
9784931455191
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1899843
handle
http://hdl.handle.net/1854/LU-1899843
date created
2011-09-11 19:48:35
date last changed
2016-12-19 15:37:39
@inproceedings{1899843,
  abstract     = {In this paper we introduce polynomial chaos in the stochastic forward model used to solve the inverse problem through Bayesian inference. We validate our approach with three different methods that construct the stochastic forward model, to treat the TEAM Workshop Problem 8.},
  author       = {De Staelen, Rob and Van Keer, Roger and Beddek, Karim and Clenet, St{\'e}phane and Moreau, Olivier},
  booktitle    = {JSAEM Studies in Applied Electromagnetics and Mechanics},
  editor       = {Rubinacci, G and Tamburrino, A and Villone, F and Takagi, T},
  isbn         = {9784931455191},
  issn         = {1343-2869},
  language     = {eng},
  location     = {Napoli, Italy},
  pages        = {525--526},
  publisher    = {IOS Press},
  title        = {Polynomial chaos forward models in Bayesian inference to solve inverse problems},
  volume       = {14},
  year         = {2011},
}

Chicago
De Staelen, Rob, Roger Van Keer, Karim Beddek, Stéphane Clenet, and Olivier Moreau. 2011. “Polynomial Chaos Forward Models in Bayesian Inference to Solve Inverse Problems.” In JSAEM Studies in Applied Electromagnetics and Mechanics, ed. G Rubinacci, A Tamburrino, F Villone, and T Takagi, 14:525–526. IOS Press.
APA
De Staelen, Rob, Van Keer, R., Beddek, K., Clenet, S., & Moreau, O. (2011). Polynomial chaos forward models in Bayesian inference to solve inverse problems. In G. Rubinacci, A. Tamburrino, F. Villone, & T. Takagi (Eds.), JSAEM Studies in Applied Electromagnetics and Mechanics (Vol. 14, pp. 525–526). Presented at the 15th International symposium on Applied Electromagnetics and Mechanics, IOS Press.
Vancouver
1.
De Staelen R, Van Keer R, Beddek K, Clenet S, Moreau O. Polynomial chaos forward models in Bayesian inference to solve inverse problems. In: Rubinacci G, Tamburrino A, Villone F, Takagi T, editors. JSAEM Studies in Applied Electromagnetics and Mechanics. IOS Press; 2011. p. 525–6.
MLA
De Staelen, Rob, Roger Van Keer, Karim Beddek, et al. “Polynomial Chaos Forward Models in Bayesian Inference to Solve Inverse Problems.” JSAEM Studies in Applied Electromagnetics and Mechanics. Ed. G Rubinacci et al. Vol. 14. IOS Press, 2011. 525–526. Print.