Deep learning for graph structured data
Graph-structured data is ubiquitous across diverse domains, representing valuable relational information between entities. However, most deep learning techniques like convolutional and recurrent neural networks are tailored for grid-structured data and struggle to handle such graphs. This has led to...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175787 |