Likelihood-informed dimension reduction for nonlinear inverse problems
The intrinsic dimensionality of an inverse problem is affected by prior information, the accuracy and number of observations, and the smoothing properties of the forward operator. From a Bayesian perspective, changes from the prior to the posterior may, in many problems, be confined to a relatively...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing,
2015-05-13T12:47:45Z.
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| Subjects: | |
| Online Access: | Get fulltext |