Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems
We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a spatial or temporal field, endowed with a hierarchical Gaussian process prior. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in th...
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Format: | Article |
Language: | English |
Published: |
Elsevier,
2010-11-04T15:31:18Z.
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Online Access: | Get fulltext |