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Graph Augmentation for Neural Networks Using Matching-Graphs
2022Mathias Fuchs, Kaspar Riesen
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Graph Contrastive Learning With Adaptive Proximity-Based Graph Augmentation
IEEE Transactions on Neural Networks and Learning SystemsGraph neural networks (GNNs) have been successful in a variety of graph-based applications. Recently, it is shown that capturing long-range relationships between nodes helps improve the performance of GNNs. The phenomenon is mostly confirmed in a supervised learning setting.
Wei Zhuo, Guang Tan
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Graph Contrastive Learning with Learnable Graph Augmentation
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023Pu, Xinyan +4 more
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Adaptive Graph Augmentation for Graph Contrastive Learning
2023Zeming Wang +3 more
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Graph Contrastive Learning with Line Graph Augmentation
2023Yan Wang +4 more
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Heterogeneous Graph Contrastive Learning with Augmentation Graph
2023Kai Yang +3 more
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Heterogeneous Graph Contrastive Learning With Augmentation Graph
IEEE Transactions on Artificial IntelligenceZijuan Zhao +4 more
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