{"id":333,"date":"2026-05-04T12:17:40","date_gmt":"2026-05-04T10:17:40","guid":{"rendered":"https:\/\/project.inria.fr\/mlsim2026\/?page_id=333"},"modified":"2026-05-07T10:37:27","modified_gmt":"2026-05-07T08:37:27","slug":"workshop","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/mlsim2026\/workshop\/","title":{"rendered":"Fall Workshop"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\">General information<\/h3>\n\n\n\n<p>The workshop&nbsp;<strong>Machine Learning + Simulation<\/strong>&nbsp;takes place from&nbsp;<strong>Monday, October 12<sup>th<\/sup>&nbsp;to Friday, October  16<sup>th<\/sup><\/strong>&nbsp; <strong>2026<\/strong>, at&nbsp;Mathematics laboratory Jean-Alexandre Dieudonn\u00e9&nbsp;at Universit\u00e9 C\u00f4te d\u2019Azur, in Valrose campus in Nice. Details on the location and venue can be found <a href=\"https:\/\/project.inria.fr\/mlsim2026\/location-and-venue\/\">here<\/a>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Topics<\/h3>\n\n\n\n<p>The worshop is focused on machine learning techniques in interaction with numerical simulations. All types of simulations are welcome and a large set of application fields is expected. The workshop covers in particular the following topics (not restrictive):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>&#8211; construction of parametric surrogate models from simulation outputs<\/li>\n\n\n\n<li>&#8211; model calibration, parameters identification and inverse problems<\/li>\n\n\n\n<li>&#8211; construction of hybrid models based on both experimental data and simulation results<\/li>\n\n\n\n<li>&#8211; deep learning for sciences (weather forecast, climate modeling, etc.)<\/li>\n\n\n\n<li>&#8211; deep learning for geometric design, geometry and mesh generation<\/li>\n\n\n\n<li>&#8211; data-based pre-treatments for simulations<\/li>\n\n\n\n<li>&#8211; generation of synthetic data<\/li>\n\n\n\n<li>&#8211; machine learning for post-treatment of simulation outputs and visualization<\/li>\n\n\n\n<li>&#8211; physics-informed machine learning<\/li>\n\n\n\n<li>&#8211; operator learning<\/li>\n\n\n\n<li>&#8211; hybridization of scientific computing and machine learning<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Call for contribution<\/h3>\n\n\n\n<p>The workshop includes contributed sessions. To apply, please send a one-page abstract before June 22<sup>nd<\/sup>. Details are <a href=\"https:\/\/project.inria.fr\/mlsim2026\/call-for-contribution\/\">here<\/a>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Registration<\/h3>\n\n\n\n<p>Participation to the workshop is free of charge, but the registration is mandatory. Details on registration can be found <a href=\"https:\/\/project.inria.fr\/mlsim2026\/registration-2\/\">here<\/a>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Program<\/h3>\n\n\n\n<p>The workshop includes keynote presentations and contributed sessions. Details are <a href=\"https:\/\/project.inria.fr\/mlsim2026\/program-2\/\" data-type=\"page\" data-id=\"349\">here<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>General information The workshop&nbsp;Machine Learning + Simulation&nbsp;takes place from&nbsp;Monday, October 12th&nbsp;to Friday, October 16th&nbsp; 2026, at&nbsp;Mathematics laboratory Jean-Alexandre Dieudonn\u00e9&nbsp;at Universit\u00e9 C\u00f4te d\u2019Azur, in Valrose campus in Nice. Details on the location and venue can be found here. Topics The worshop is focused on machine learning techniques in interaction with numerical\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/mlsim2026\/workshop\/\"><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-333","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages\/333","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=333"}],"version-history":[{"count":5,"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages\/333\/revisions"}],"predecessor-version":[{"id":352,"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/pages\/333\/revisions\/352"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/mlsim2026\/wp-json\/wp\/v2\/media?parent=333"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}