Self-Supervised Hypergraph Learning for Enhanced Multimodal Representation
Hypergraph neural networks have gained substantial popularity in capturing complex correlations between data items in multimodal datasets. In this study, we propose a novel approach called the self-supervised hypergraph learning (SHL) framework that focuses on extracting hypergraph features to impro...
| Published in: | IEEE Access |
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| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10418926/ |