Physics inspired models in artificial intelligence

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dc.authoridŞener Özönder / 0000-0001-5471-6512en_US
dc.authorscopusidŞener Özönder / 36144435300
dc.authorwosidŞener Özönder / FQP-9984-2022
dc.contributor.authorAhmad, Muhammad Aurangzeb
dc.contributor.authorÖzönder, Şener
dc.date.accessioned2020-09-15T06:43:58Z
dc.date.available2020-09-15T06:43:58Z
dc.date.issued2020en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Bölümüen_US
dc.description.abstractAbstract Ideas originating in physics have informed progress in artificial intelligence and machine learning for many decades. However the pedigree of many such ideas is oft neglected in the Computer Science community. The tutorial focuses on current and past ideas from physics that have helped in furthering AI and machine learning. Recent advances in physics inspired ideas in AI are also explored especially how insights from physics may hold the promise of opening the black box of deep learning. Lastly, current and future trends in this area and outlines of a research agenda on how physics-inspired models can benefit AI machine learning is given.en_US
dc.identifier.citationAhmad, M. A., & Özönder, Ş. (2020, August). Physics Inspired Models in Artificial Intelligence. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 3535-3536).en_US
dc.identifier.doi10.1145/3394486.3406464en_US
dc.identifier.endpage3536en_US
dc.identifier.isbn978-145037998-4
dc.identifier.scopus2-s2.0-85090425311en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage3535en_US
dc.identifier.urihttps://doi.org/10.1145/3394486.3406464
dc.identifier.urihttps://hdl.handle.net/20.500.12713/1019
dc.identifier.wosWOS:000749552303073en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÖzönder, Şener
dc.language.isoenen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.ispartofProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Miningen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAi and Physicsen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectMachine Learning and Physicsen_US
dc.subjectPhysicsen_US
dc.subjectPhysics Inspired Modelsen_US
dc.titlePhysics inspired models in artificial intelligenceen_US
dc.typeConference Objecten_US

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