{"id":250,"date":"2026-03-02T15:16:50","date_gmt":"2026-03-02T14:16:50","guid":{"rendered":"https:\/\/project.inria.fr\/mlsim2026\/?page_id=250"},"modified":"2026-03-17T15:21:52","modified_gmt":"2026-03-17T14:21:52","slug":"program","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/mlsim2026\/program\/","title":{"rendered":"Program"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Lectures<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Fr\u00e9d\u00e9ric Pr\u00e9cioso<\/strong>: <em>introductory tutorial on machine learning<\/em><\/li>\n\n\n\n<li><strong>Patrick Gallinari<\/strong>: <em>data-driven modeling<\/em><\/li>\n\n\n\n<li><strong>Laurent Navoret &amp; R\u00e9mi Imbach<\/strong>: <em>physics-informed machine learning<\/em><\/li>\n\n\n\n<li><strong>Laurent Cordier<\/strong>: <em>reduced-order models and reinforcement learning for control<\/em><\/li>\n\n\n\n<li><strong>Bertrand Iooss &amp; Alejandro Ribes<\/strong>: <em>Machine learning-based metamodels for emulating industrial costly simulations and solving inverse problems<\/em><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Detailed schedule<\/h2>\n\n\n\n<p>A draft program is proposed below, which may however be subject to slight modifications. <\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\"><\/div>\n<\/div>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-fixed-layout\"><thead><tr><th class=\"has-text-align-center\" data-align=\"center\"><\/th><th class=\"has-text-align-center\" data-align=\"center\">Mon., May 18th<\/th><th class=\"has-text-align-center\" data-align=\"center\">Tues., May 19th<\/th><th class=\"has-text-align-center\" data-align=\"center\">Wed., May 20th<\/th><th class=\"has-text-align-center\" data-align=\"center\">Thur., May 21st<\/th><th class=\"has-text-align-center\" data-align=\"center\">Fri., May 22nd<\/th><\/tr><\/thead><tbody><tr><td class=\"has-text-align-center\" data-align=\"center\">9h &#8211; 10h30<\/td><td class=\"has-text-align-center\" data-align=\"center\">Welcome<\/td><td class=\"has-text-align-center\" data-align=\"center\">Data-driven modeling<br>(P. Gallinari)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Physics-informed learning<br>(L. Navoret &amp; R. Imbach)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Reinforcement learning<br>(L. Cordier)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Reinforcement learning<br>(L. Cordier)<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">10h30 &#8211; 11h<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">11h &#8211; 12h<\/td><td class=\"has-text-align-center\" data-align=\"center\">Introductory tutorial<br>(F. Pr\u00e9cioso)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Data-driven modeling<br>(P. Gallinari)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Physics-informed learning<br>(L. Navoret &amp; R. Imbach)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Reinforcement learning<br>(L. Cordier)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Reinforcement learning<br>(L. Cordier)<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">12h &#8211; 14h<\/td><td class=\"has-text-align-center\" data-align=\"center\">Lunch<\/td><td class=\"has-text-align-center\" data-align=\"center\">Lunch<\/td><td class=\"has-text-align-center\" data-align=\"center\">Lunch<\/td><td class=\"has-text-align-center\" data-align=\"center\">Lunch<\/td><td class=\"has-text-align-center\" data-align=\"center\">Lunch<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">14h &#8211; 15h30<\/td><td class=\"has-text-align-center\" data-align=\"center\">Introductory tutorial<br>(F. Pr\u00e9cioso)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Data-driven modeling<br>(P. Gallinari)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Physics-informed learning<br>(L. Navoret &amp; R. Imbach)<\/td><td class=\"has-text-align-center\" data-align=\"center\">ML-based metamodels<br>(B. Iooss &amp; A. Ribes)<\/td><td class=\"has-text-align-center\" data-align=\"center\"><\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">15h30 &#8211; 16h<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\">Coffee break<\/td><td class=\"has-text-align-center\" data-align=\"center\"><\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">16h &#8211; 17h<\/td><td class=\"has-text-align-center\" data-align=\"center\">Introductory tutorial<br>(F. Pr\u00e9cioso)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Data-driven modeling<br>(P. Gallinari)<\/td><td class=\"has-text-align-center\" data-align=\"center\">Physics-informed learning<br>(L. Navoret &amp; R. Imbach)<\/td><td class=\"has-text-align-center\" data-align=\"center\">ML-based metamodels<br>(B. Iooss &amp; A. Ribes)<\/td><td class=\"has-text-align-center\" data-align=\"center\"><\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Lectures Detailed schedule A draft program is proposed below, which may however be subject to slight modifications. Mon., May 18th Tues., May 19th Wed., May 20th Thur., May 21st Fri., May 22nd 9h &#8211; 10h30 Welcome Data-driven modeling(P. Gallinari) Physics-informed learning(L. Navoret &amp; R. Imbach) Reinforcement learning(L. Cordier) Reinforcement learning(L.\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/mlsim2026\/program\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":2374,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-250","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages\/250","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/users\/2374"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/comments?post=250"}],"version-history":[{"count":6,"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages\/250\/revisions"}],"predecessor-version":[{"id":291,"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages\/250\/revisions\/291"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/media?parent=250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}