{"id":58,"date":"2019-03-19T18:14:43","date_gmt":"2019-03-19T18:14:43","guid":{"rendered":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/?p=58"},"modified":"2019-03-19T18:14:43","modified_gmt":"2019-03-19T18:14:43","slug":"next-session-27-03-multilevel-monte-carlo","status":"publish","type":"post","link":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/2019\/03\/19\/next-session-27-03-multilevel-monte-carlo\/","title":{"rendered":"Next session &#8211; 27\/03 &#8211; Multilevel Monte-Carlo"},"content":{"rendered":"<p>Next session: <b>Wednesday 27th March<\/b>, with an exciting paper on a topic new to us!<\/p>\n<p>Paper: &#8220;Multilevel Monte Carlo methods&#8221;, M. B. Giles, Acta Numerica, 2015, vol. 24, pp. 259-328<\/p>\n<p><a href=\"https:\/\/www.cambridge.org\/core\/journals\/acta-numerica\/article\/multilevel-monte-carlo-methods\/C5AF9A57ED8FF8FDF08074C1071C5511\">https:\/\/www.cambridge.org\/core\/journals\/acta-numerica\/article\/multilevel-monte-carlo-methods\/C5AF9A57ED8FF8FDF08074C1071C5511<\/a><\/p>\n<p>Monte Carlo (MC) methods are a very general and useful approach for the estimation of expectations arising from stochastic simulation. However, they can be computationally **very** expensive. Multilevel Monte Carlo is a recently developed approach which greatly reduces the computational cost by performing most simulations with low accuracy at a correspondingly low cost, with relatively few simulations being performed at high accuracy and a high cost. This article reviews the ideas behind multilevel MC, and various cool applications.<\/p>\n<p>Very relevant for infectious disease modeling!<\/p>\n<p>Presenter: Juliette Unwin<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Next session: Wednesday 27th March, with an exciting paper on a topic new to us! Paper: &#8220;Multilevel Monte Carlo methods&#8221;, M. B. Giles, Acta Numerica, 2015, vol. 24, pp. 259-328 https:\/\/www.cambridge.org\/core\/journals\/acta-numerica\/article\/multilevel-monte-carlo-methods\/C5AF9A57ED8FF8FDF08074C1071C5511 Monte Carlo (MC) methods are a very general and useful approach for the estimation of expectations arising from stochastic simulation. However, they can be [&hellip;]<\/p>\n","protected":false},"author":1190,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-58","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/58","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/users\/1190"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/comments?post=58"}],"version-history":[{"count":1,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/58\/revisions"}],"predecessor-version":[{"id":59,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/posts\/58\/revisions\/59"}],"wp:attachment":[{"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/media?parent=58"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/categories?post=58"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs-staging.imperial.ac.uk\/smh-stats-reading-group\/wp-json\/wp\/v2\/tags?post=58"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}