Data-Driven Forward Discretizations for Bayesian Inversion
© 2020 IOP Publishing Ltd. This paper suggests a framework for the learning of discretizations of expensive forward models in Bayesian inverse problems. The main idea is to incorporate the parameters governing the discretization as part of the unknown to be estimated within the Bayesian machinery. W...
Main Authors: | Bigoni, D, Chen, Y, Trillos, N Garcia, Marzouk, Y, Sanz-Alonso, D |
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Other Authors: | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2021
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Online Access: | https://hdl.handle.net/1721.1/134038 |
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