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Polynomial chaos forward models in Bayesian inference to solve inverse problems

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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.

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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.
@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},
}