[et_pb_section fb_built=”1″ _builder_version=”3.22″][et_pb_row _builder_version=”3.22″ background_size=”initial” background_position=”top_left” background_repeat=”repeat”][et_pb_column type=”1_4″ _builder_version=”3.0.47″][et_pb_text _builder_version=”3.22.1″ background_color=”#072c72″ border_color_all=”#3255c9″ text_orientation=”right” background_layout=”dark” custom_padding=”20px|15px|15px|” z_index_tablet=”500″]<\/p>\n
2024 <\/em><\/p>\n Strategic Projects<\/em><\/p>\n @Physics\/Astronomy<\/span><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”3.22.1″ text_orientation=”right” z_index_tablet=”500″]<\/p>\n #Self-supervised Learning<\/p>\n #Semi-supervised Learning<\/p>\n #Sensitivity enhancement<\/p>\n #Data Analysis based on AI<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”3.0.47″][et_pb_text _builder_version=”3.22.1″ z_index_tablet=”500″]<\/p>\n The aim of the ADAPT project was to develop a novel analysis strategy for the KM3NeT astroparticle physics experiment, using semi-supervised learning, to minimise the dependence on labelled data coming from Monte Carlo simulations. KM3NeT, a neutrino telescope located deep in the Mediterranean Sea, consists of a 3D array of Cherenkov light detectors that capture the passage of charged particles induced by neutrino interactions. A key challenge in KM3NeT data analysis is the substantial light background caused by K40 decays in seawater, which surrounds each neutrino-induced event. We will present our results on the implementation of this innovative analysis strategy.<\/p>\n <\/p>\n Ankur Sharma [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_margin=”120px||” admin_label=”Row” _builder_version=”3.22.1″ locked=”off”][et_pb_column type=”4_4″ _builder_version=”3.22.1″][et_pb_divider _builder_version=”3.22.1″][\/et_pb_divider][et_pb_text admin_label=”\u00c0 lire aussi” _builder_version=”3.22.1″ z_index_tablet=”500″ locked=”off”]<\/p>\n [\/et_pb_text][et_pb_blog posts_number=”4″ include_categories=”37″ show_author=”off” show_date=”off” show_pagination=”off” module_id=”page_type_blog” _builder_version=”3.22.1″ header_level=”h4″ border_width_bottom_fullwidth=”1px” border_color_bottom_fullwidth=”rgba(51,51,51,0.18)” custom_padding=”||50px|” z_index_tablet=”500″ locked=”off”][\/et_pb_blog][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" 2024 Strategic Projects @Physics\/Astronomy #Self-supervised Learning#Semi-supervised Learning#Sensitivity enhancement#Data Analysis based on AI Project Summary The aim of the ADAPT project was to develop a novel analysis strategy for the KM3NeT astroparticle physics experiment, using semi-supervised learning, to minimise the dependence on labelled data coming from Monte Carlo simulations. KM3NeT, a neutrino telescope located deep in… Lire la suite Accelerate Discoveries (boosting) Astroparticle Physics (analysis) Techniques – ADAPT<\/span><\/a><\/p>\n","protected":false},"author":560,"featured_media":2263,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[51,1,37,26],"tags":[],"class_list":["post-1500","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-51","category-diip","category-physics-astronomy","category-strategic-projects"],"_links":{"self":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/1500","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/users\/560"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/comments?post=1500"}],"version-history":[{"count":6,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/1500\/revisions"}],"predecessor-version":[{"id":3136,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/1500\/revisions\/3136"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/media\/2263"}],"wp:attachment":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/media?parent=1500"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/categories?post=1500"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/tags?post=1500"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Project Summary<\/strong><\/h3>\n
Yvonne Becherini
<\/strong>yvonne.becherini@wordpress-test.app.u-pariscite.fr<\/span><\/h3>\n\n
<\/strong>Pranju Goswami
<\/strong>Maximilian Eff
<\/strong>Enzo Oukacha<\/strong><\/p>\nProjects in the same discipline
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