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master's thesis
Zaključivanje nad grafovima metodama dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:199677
Rakovac, Daniel
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Rakovac, D. (2020). Zaključivanje nad grafovima metodama dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:199677

Rakovac, Daniel. "Zaključivanje nad grafovima metodama dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:199677

Rakovac, Daniel. "Zaključivanje nad grafovima metodama dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:199677

Rakovac, D. (2020). 'Zaključivanje nad grafovima metodama dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:199677

Rakovac D. Zaključivanje nad grafovima metodama dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 May 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:199677

D. Rakovac, "Zaključivanje nad grafovima metodama dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:199677

Metadata
TitleZaključivanje nad grafovima metodama dubokog učenja
Title (english)Reasoning on Graphs based on Deep Learning Methods
AuthorDaniel Rakovac
MentorMarko Čupić (mentor)
Committee memberMarko Čupić (predsjednik povjerenstva)
Committee memberŽeljka Mihajlović (član povjerenstva)
Committee memberMarko Đurasević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom je radu obrađena primjena dubokog učenja na zaključivanje nad grafovima. Na početku rada su objašnjeni osnovni pojmovi teorije grafova i ključni modeli dubokog učenja. Mnogi modeli definirani nad grafovima su samo modifikacije dubokih modela koje koristimo u ostalim područjima. Odabrana su tri modela za zaključivanje nad grafovima, to su konvolucijska mreža grafova, neuronska mreža grafova s pažnjom, te generativni suparnički model NetGAN. Primijenjeni su na problem klasifikacije čvorova i grafova, te na problem generiranja grafova. Za evaluaciju modela odabrane su tri citacijske mreže i skup grafova koji predstavljaju strukture proteina. Proveden je niz eksperimenata zbog ispitivanja utjecaja parametara na rezultate modela.
Abstract (english)
This paper describes the application of deep learning methods for reasoning on graphs. At the beginning of the paper, the base terms of graphs theory and key deep learning models are explained. Many models defined on graphs are just modifications of deep models used in other areas. Three models are selected for reasoning on graphs, convolutional graph network, graph attention network, and generative adversarial model NetGAN. They are applied to the problem of node and graph classification and graph generation. For evaluating the models, three citation networks and one graph set which contains protein structures are used. A series of experiments are conducted for exploring parameters influence on model results.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:199677
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-13 13:40:32