Parallel Local Approximation MCMC for Expensive Models
Performing Bayesian inference via Markov chain Monte Carlo (MCMC) can be exceedingly expensive when posterior evaluations invoke the evaluation of a computationally expensive model, such as a system of PDEs. In recent work [J. Amer. Statist. Assoc., 111 (2016), pp. 1591-1607] we described a framewor...
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Bibliographic Details
| Main Authors: |
Conrad, Patrick Raymond
(Contributor),
Davis, Andrew Donaldson
(Contributor),
Marzouk, Youssef M
(Contributor),
Pillai, Natesh S
(Contributor),
Smith, Aaron Robin
(Contributor) |
|---|
| Other Authors: |
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
(Contributor),
Massachusetts Institute of Technology. Department of Mechanical Engineering
(Contributor),
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
(Contributor),
Massachusetts Institute of Technology. Computation for Design and Optimization Program
(Contributor),
MIT Kavli Institute for Astrophysics and Space Research
(Contributor) |
|---|
| Format: | Article
|
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| Language: | English |
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| Published: |
Society for Industrial & Applied Mathematics (SIAM),
2019-03-11T14:58:03Z.
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| Subjects: | |
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| Online Access: | Get fulltext
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