{"id":992,"date":"2024-10-31T19:04:25","date_gmt":"2024-10-31T19:04:25","guid":{"rendered":"https:\/\/pages.lip.pt\/pheno\/?p=992"},"modified":"2024-11-04T10:57:04","modified_gmt":"2024-11-04T10:57:04","slug":"machine-learning-for-jet-physics-2024-ml4jets2024","status":"publish","type":"post","link":"https:\/\/pages.lip.pt\/pheno\/uncategorized\/machine-learning-for-jet-physics-2024-ml4jets2024\/","title":{"rendered":"Machine Learning for Jet Physics 2024 (ML4Jets2024)"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"684\" src=\"https:\/\/pages.lip.pt\/pheno\/wp-content\/uploads\/sites\/29\/2024\/10\/afsgasfga-1-1024x684.jpeg\" alt=\"\" class=\"wp-image-994\" style=\"width:476px;height:auto\" srcset=\"https:\/\/pages.lip.pt\/pheno\/wp-content\/uploads\/sites\/29\/2024\/10\/afsgasfga-1-1024x684.jpeg 1024w, https:\/\/pages.lip.pt\/pheno\/wp-content\/uploads\/sites\/29\/2024\/10\/afsgasfga-1-300x200.jpeg 300w, https:\/\/pages.lip.pt\/pheno\/wp-content\/uploads\/sites\/29\/2024\/10\/afsgasfga-1-768x513.jpeg 768w, https:\/\/pages.lip.pt\/pheno\/wp-content\/uploads\/sites\/29\/2024\/10\/afsgasfga-1-1536x1026.jpeg 1536w, https:\/\/pages.lip.pt\/pheno\/wp-content\/uploads\/sites\/29\/2024\/10\/afsgasfga-1-2048x1367.jpeg 2048w\" sizes=\"(max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px\" \/><\/figure>\n<\/div>\n\n\n<p style=\"font-size:15px\">Machine learning has become a hot topic in particle physics over the past several years. In particular, there has been a lot of progress in the areas of particle and event identification, reconstruction, generative models, anomaly detection and more. In this conference, we will discuss current progress in these areas, focusing on new breakthrough ideas and existing challenges.<\/p>\n\n\n\n<p style=\"font-size:15px\">The ML4Jets workshop will be open to the full community and will include LHC experiments as well as theorists and phenomenologists interested in this topic. We explicitly welcome contributions and participation from method scientists as well as adjacent scientific fields such as astronomy, astrophysics, astroparticle physics, hadron and nuclear physics and other domains facing similar challenges.<\/p>\n\n\n\n<p style=\"font-size:15px\">The program will cover the following topics:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li style=\"font-size:15px\">Tagging (Classification)<\/li>\n\n\n\n<li style=\"font-size:15px\">Reconstruction<\/li>\n\n\n\n<li style=\"font-size:15px\">Detector simulation &amp; event generation<\/li>\n\n\n\n<li style=\"font-size:15px\">Theory<\/li>\n\n\n\n<li style=\"font-size:15px\">Astrophysics<\/li>\n\n\n\n<li style=\"font-size:15px\">Unfolding<\/li>\n\n\n\n<li style=\"font-size:15px\">Uncertainties<\/li>\n\n\n\n<li style=\"font-size:15px\">Anomaly detection<\/li>\n\n\n\n<li style=\"font-size:15px\">Interpretability<\/li>\n<\/ul>\n\n\n\n<p style=\"font-size:15px\">This year&#8217;s conference is organised jointly by LPNHE, LPTHE and IJCLab and hosted by LPNHE on the Paris Sorbonne Campus. <strong>Registration for both in-person and Zoom-participation is open and free of charge<\/strong>. It will take place from the <strong>4th<\/strong> to <strong>8th of November<\/strong>.<\/p>\n\n\n\n<p>INDICO page: <a href=\"https:\/\/indico.cern.ch\/event\/1386125\/\" data-type=\"link\" data-id=\"https:\/\/indico.cern.ch\/event\/1386125\/\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/indico.cern.ch\/event\/1386125\/<\/a><\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#8dd2fc4d;font-size:15px\">One of our PhD students, Jo\u00e3o Gon\u00e7alves, will attend and deliver a talk.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine learning has become a hot topic in particle physics over the past several years. In particular, there has been a lot of progress in the areas of particle and event identification, reconstruction, generative models, anomaly detection and more. In this conference, we will discuss current progress in these areas, focusing on new breakthrough ideas &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/pages.lip.pt\/pheno\/uncategorized\/machine-learning-for-jet-physics-2024-ml4jets2024\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Machine Learning for Jet Physics 2024 (ML4Jets2024)&#8221;<\/span><\/a><\/p>\n","protected":false},"author":33,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-992","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/posts\/992","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/users\/33"}],"replies":[{"embeddable":true,"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/comments?post=992"}],"version-history":[{"count":3,"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/posts\/992\/revisions"}],"predecessor-version":[{"id":1003,"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/posts\/992\/revisions\/1003"}],"wp:attachment":[{"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/media?parent=992"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/categories?post=992"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pages.lip.pt\/pheno\/wp-json\/wp\/v2\/tags?post=992"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}