A Lightweight Method for Graph Neural Networks Based on Knowledge Distillation and Graph Contrastive Learning
Graph neural networks (GNNs) are crucial tools for processing non-Euclidean data. However, due to scalability issues caused by the dependency and topology of graph data, deploying GNNs in practical applications is challenging. Some methods aim to address this issue by transferring GNN knowledge to M...
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| Glavni autori: | , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
MDPI AG
2024-06-01
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| Serija: | Applied Sciences |
| Teme: | |
| Online pristup: | https://www.mdpi.com/2076-3417/14/11/4805 |
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