Geometric MCMC for infinite-dimensional inverse problems
نویسندگان
چکیده
منابع مشابه
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 accurate. Such methods are typically forced to reduce step-sizes as the discretization gets finer, and t...
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ژورنال
عنوان ژورنال: Journal of Computational Physics
سال: 2017
ISSN: 0021-9991
DOI: 10.1016/j.jcp.2016.12.041