Betancourt, Michael, Byrne, Simon, Livingstone, Sam and Girolami, Mark (2017) The geometric foundations of Hamiltonian Monte Carlo. Bernoulli, 23 (4A). pp. 2257-2298. doi:10.3150/16-BEJ810 ISSN 1350-7265.

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Abstract

Although Hamiltonian Monte Carlo has proven an empirical success, the lack of a rigorous theoretical understanding of the algorithm has in many ways impeded both principled developments of the method and use of the algorithm in practice. In this paper we develop the formal foundations of the algorithm through the construction of measures on smooth manifolds, and demonstrate how the theory naturally identifies efficient implementations and motivates promising generalizations.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science, Engineering and Medicine > Science > Statistics
Library of Congress Subject Headings (LCSH):	Markov processes, Hamiltonian systems, Geometry, Differential, Geometry, Riemannian, Symplectic geometry
Journal or Publication Title:	Bernoulli
Publisher:	Int Statistical Institute
ISSN:	1350-7265
Official Date:	9 May 2017
Dates:	Date Event 9 May 2017 Published 8 January 2016 Accepted
Volume:	23
Number:	4A
Page Range:	pp. 2257-2298
DOI:	10.3150/16-BEJ810
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	11 April 2016
Date of first compliant Open Access:	12 April 2016
Related URLs:	Publisher

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