Understanding graph neural networks
Camerlengo, Vincenzo (A.A. 2024/2025) Understanding graph neural networks. Tesi di Laurea in Big data and smart data analytics, Luiss Guido Carli, relatore Irene Finocchi, pp. 78. [Master's Degree Thesis]
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Abstract/Index
Graph neural networks. Graph theory fundamentals. Basics of neural networks. Graph neural networks. Advanced models of GNN. Real-world applications of GNN. Case study. Overview of the case study. Dataset description. Exploratory analysis. Data processing. Model training. Model performance. Metrics. Inference.
References
Bibliografi: pp. 76-78.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Big data and smart data analytics |
| Thesis Supervisor: | Finocchi, Irene |
| Thesis Co-Supervisor: | Sinaimeri, Blerina |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 18 Mar 2026 16:16 |
| Last Modified: | 18 Mar 2026 16:16 |
| URI: | https://tesi.luiss.it/id/eprint/45174 |
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