Improving representation learning on graph-structural data for classification, generation, and recommendation
This thesis explores innovative approaches in graph representation learning and its applications using deep learning models, making significant contributions across several key areas. We first introduce the Graph Meta-Contrast (GMeCo) framework, a novel meta-learning framework for contrastive repres...
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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/10356/179453 |