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undergraduate thesis
Klasifikacija uz graf neuronske mreže
2024. urn:nbn:hr:126:766590
Klaić, Marko
Josip Juraj Strossmayer University of Osijek
School of Applied Mathematics and Informatics

Cite this document

Klaić, M. (2024). Klasifikacija uz graf neuronske mreže (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics. Retrieved from https://urn.nsk.hr/urn:nbn:hr:126:766590

Klaić, Marko. "Klasifikacija uz graf neuronske mreže." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, 2024. https://urn.nsk.hr/urn:nbn:hr:126:766590

Klaić, Marko. "Klasifikacija uz graf neuronske mreže." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, 2024. https://urn.nsk.hr/urn:nbn:hr:126:766590

Klaić, M. (2024). 'Klasifikacija uz graf neuronske mreže', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, accessed 23 December 2024, https://urn.nsk.hr/urn:nbn:hr:126:766590

Klaić M. Klasifikacija uz graf neuronske mreže [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics; 2024 [cited 2024 December 23] Available at: https://urn.nsk.hr/urn:nbn:hr:126:766590

M. Klaić, "Klasifikacija uz graf neuronske mreže", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:126:766590

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Metadata
TitleKlasifikacija uz graf neuronske mreže
Title (english)Classification with Graph Neural Network
AuthorMarko Klaić
MentorDomagoj Ševerdija (mentor)
GranterJosip Juraj Strossmayer University of Osijek
School of Applied Mathematics and Informatics
Osijek
Defense date and country2024-09-17, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U posljednjih nekoliko godina graf neuronske mreže dobivaju sve veću pažnju te se sukladno s tim razvijaju velikom brzinom. Graf neuronske mreže su postale moćni i praktični alati za zadatke strojnog učenja u domeni grafova. Napredak je zasnovan najviše na izražajnoj snazi, algoritmima za treniranje te na fleksibilnosti modela. U industriji su se tek nedavno krenule koristiti primjene strojnog učenja s grafovima, međutim, graf neuronske mreže su se odmah počele koristiti u različitim domenama te u najsuvremenijim modelima. U budućnosti možemo samo očekivati još veću kvalitetu te korist graf neuronskih mreža u još većem broju grana.
Abstract (english)
In the last few years, graph neural networks have been receiving more and more attention and, accordingly, are developing at a high speed. Graph neural networks have become powerful and practical tools for machine learning tasks in the graph domain. Progress is based mostly on expressive power, training algorithms and model flexibility. Machine learning applications with graphs have only recently begun to be used in industry, however, graph neural networks have immediately begun to be used in various domains and in stateof-the-art models. In the future, we can only expect even greater quality and benefit of graph neural networks in an even greater number of branches.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:126:766590
Study programmeTitle: Bachelor of Mathematics and Computer Science
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike i računarstva (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike i računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
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Created on2024-09-20 11:19:49