A stable manifold MCMC method for high dimensions
Copyright policy )A stable manifold MCMC method for high dimensions
We combine two important recent advancements of MCMC algorithms: first, methods utilizing the intrinsic manifold structure of the parameter space; then, algorithms effective for targets in infinite-dimensions with the critical property that their mixing time is robust to mesh refinement.
- National University of Singapore Singapore
- University College London United Kingdom
infinite dimensions, FOS: Computer and information sciences, metropolis-adjusted Langevin algorithm, Methodology (stat.ME), Cameron-Martin space, Infinite dimensions, Computational methods in Markov chains, manifold MCMC, Manifold MCMC, Metropolis-adjusted langevin algorithm, Statistics - Methodology
infinite dimensions, FOS: Computer and information sciences, metropolis-adjusted Langevin algorithm, Methodology (stat.ME), Cameron-Martin space, Infinite dimensions, Computational methods in Markov chains, manifold MCMC, Manifold MCMC, Metropolis-adjusted langevin algorithm, Statistics - Methodology
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