Masked autoencoders for contrastive learning of heterogenous graphs
In this data driven society, information networks are mostly heterogenous which consists of different types of entities and relationships. Heterogenous Graph Neural Networks utilize Heterogenous graphs to study and understand the data. Since Heterogenous Graph Neural Network uses semi-supervised lea...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/176838 |