Geometric MCMC for infinite-dimensional inverse problems
Bayesian inverse problems often involve sampling posterior distributions on infinite-dimensional function spaces. Traditional Markov chain Monte Carlo (MCMC) algorithms are characterized by deteriorating mixing times upon meshrefinement, when the finite-dimensional approximations become more accurat...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Published: |
Elsevier
2016
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