{"id":43784,"date":"2026-11-13T10:59:21","date_gmt":"2026-11-13T10:59:21","guid":{"rendered":"https:\/\/lamarr-institute.org\/publication\/deep-learning-discovery-algorithms-in-high-energy-physics-and-the-conflict-between-model-independence-and-robustness\/"},"modified":"2026-11-13T10:59:21","modified_gmt":"2026-11-13T10:59:21","slug":"deep-learning-discovery-algorithms-in-high-energy-physics-and-the-conflict-between-model-independence-and-robustness","status":"publish","type":"publication","link":"https:\/\/lamarr-institute.org\/de\/publication\/deep-learning-discovery-algorithms-in-high-energy-physics-and-the-conflict-between-model-independence-and-robustness\/","title":{"rendered":"Deep {Learning} {Discovery} {Algorithms} in {High}-{Energy} {Physics} and the {Conflict} {Between} {Model}-{Independence} and {Robustness}"},"content":{"rendered":"<p>Machine Learning models have become widely recognized for their potential to revolutionize science. In High-Energy Physics, they are of particular promise in propelling the field forward by fueling experimental discoveries. State-of-the-art uses of Machine Learning are considered {&#8218;model-independent&#8216;}  by the High-Energy Physics community; a verdict shared by several philosophers. In this paper, we dig into the details of unsupervised anomaly detection and show that even modest senses of model-independence are doubt-worthy, once considerations of robustness are factored in. We also offer reasons to think that the theme generalizes beyond the narrow context of High-Energy Physics.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine Learning models have become widely recognized for their potential to revolutionize science. In High-Energy Physics, they are of particular promise in propelling the field forward by fueling experimental discoveries. State-of-the-art uses of Machine Learning are considered {&#8218;model-independent&#8216;} by the High-Energy Physics community; a verdict shared by several philosophers. In this paper, we dig into the details of unsupervised anomaly detection and show that even modest senses of model-independence are [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"publication-type":[30],"publication-year":[1680],"class_list":["post-43784","publication","type-publication","status-publish","hentry","publication-type-article","publication-year-1680"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/43784","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication"}],"about":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/types\/publication"}],"author":[{"embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/users\/14"}],"version-history":[{"count":0,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/43784\/revisions"}],"wp:attachment":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/media?parent=43784"}],"wp:term":[{"taxonomy":"publication-type","embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication-type?post=43784"},{"taxonomy":"publication-year","embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication-year?post=43784"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}