{"id":45023,"date":"2022-02-02T11:22:27","date_gmt":"2022-02-02T10:22:27","guid":{"rendered":"https:\/\/www.h-its.org\/de\/event\/hits-simplaix-joint-colloquium-frank-noe-deep-learning-for-molecular-physics-and-chemistry\/"},"modified":"2026-01-26T11:21:21","modified_gmt":"2026-01-26T10:21:21","slug":"hits-simplaix-joint-colloquium-frank-noe","status":"publish","type":"tribe_events","link":"https:\/\/www.h-its.org\/de\/event\/hits-simplaix-joint-colloquium-frank-noe\/","title":{"rendered":"HITS-SIMPLAIX joint colloquium Frank No\u00e9: Deep Learning for Molecular Physics and Chemistry"},"content":{"rendered":"<p>By <a href=\"https:\/\/www.mi.fu-berlin.de\/en\/math\/groups\/ai4s\/staff\/noe\/index.html\">Frank No\u00e9<\/a>, Freie Universit\u00e4t Berlin, Fachbereich Mathematik und Informatik<\/p>\n<p>AI, and specifically deep ML methods have a profound impact on industry and information technology. But since recently AI methods are also changing the way we do science. In this talk I will present some of our recent efforts to build machine learning methods that attack fundamental problems in physical and chemical sciences: the sampling problem in physical many-body systems, and the solution of the quantum-chemical electronic Schr\u00f6dinger equation. Key in making progress in these hard problems with ML is to interrogate the physical system about what the learning problem should be, and to encode physical structures, such as symmetries and conservation laws, into the ML model.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><strong>REGISTRATION:<\/strong><\/p>\n<article>The colloquium is taking place via Zoom.<\/article>\n<article>Please register in advance for this meeting: <a href=\"https:\/\/kta-email.zoom.us\/meeting\/register\/tJ0lduutrzkrH9SzLBrAxFA_e3VI2377Ttdq\">https:\/\/kta-email.zoom.us\/meeting\/register\/tJ0lduutrzkrH9SzLBrAxFA_e3VI2377Ttdq<\/a><\/article>\n<article>After registering, you will receive a confirmation email containing information about joining the meeting.<\/article>\n<article><\/article>\n<article><\/article>\n<article>In case you are not able to attend, you can watch the talk afterwards on the HITS YouTube channel:\u00a0<a href=\"https:\/\/www.youtube.com\/user\/TheHITSters\" target=\"_blank\" rel=\"noopener noreferrer\" data-fancybox-group=\"fb_gallery_0_0\">https:\/\/www.youtube.com\/user\/TheHITSters<\/a>.<\/article>\n","protected":false},"excerpt":{"rendered":"<p>By Frank No\u00e9, Freie Universit\u00e4t Berlin, Fachbereich Mathematik und Informatik AI, and specifically deep ML methods have a profound impact &#8230;<\/p>\n","protected":false},"author":42,"featured_media":45025,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"hits-research-group":[1319,1298,1422],"tribe_events_cat":[1345,1408],"class_list":["post-45023","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","hits-research-group-hits","hits-research-group-mcm-de","hits-research-group-simplaix","tribe_events_cat-oeffentliche-veranstaltungen","tribe_events_cat-kolloquien","cat_oeffentliche-veranstaltungen","cat_kolloquien"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - 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