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MCMC methods in high dimension.

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Beskos, Alexandros, Roberts, Gareth O., Sanz-Serna, Chus, Stuart, A. M., Pillai, Natesh S. and Pinski, F. J. (2009) MCMC methods in high dimension. In: 2009-10 Program on Stochastic Dynamics Opening Tutorials & Workshops, Raleigh, NC, 30 Aug-2 Sep 2009 ISBN 978-0-7354-0709-1.

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Official URL: http://legacy.samsi.info/workshops/2009stodyn-open...

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Abstract

I will overview recent work concerning the design and analysis of Hybrid Monte Carlo (HMC) methods for the sampling of high or infinite dimensional probability measures. In particular I will show
(i) how the standard HMC method should be scaled for a wide class of high dimensional problems; and
(ii) how to circumvent these scaling issues for problems where the target measure has a density with respect to a Gaussian measure.

Item Type: Conference Item (Paper)
Subjects: Q Science > QC Physics
Divisions: Faculty of Science, Engineering and Medicine > Science > Mathematics
Faculty of Science, Engineering and Medicine > Science > Statistics
Series Name: AIP Conference Proceedings
ISBN: 978-0-7354-0709-1
Editor: Simos, TE and Psihoyios, G and Tsitouras, C
Official Date: September 2009
Dates:
DateEvent
September 2009Completion
Number of Pages: 3
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Description:

Presented by A. M. Stuart

Version or Related Resource: Beskos, Alexandros, et al. (2009). MCMC methods in high dimension. In: Newton Institute : SPDE Opening Workshop. Cambridge, 7 Jan 2010. Beskos, Alexandros, et al. (2009). The Hybrid Monte Carlo Algorithm in High Dimensions. In: Simulation of hybrid dynamical systems and applications to molecular dynamics. Paris, 27-30th Sep 2010.
Conference Paper Type: Paper
Title of Event: 2009-10 Program on Stochastic Dynamics Opening Tutorials & Workshops
Type of Event: Conference
Location of Event: Raleigh, NC
Date(s) of Event: 30 Aug-2 Sep 2009
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