Attention-based stackable graph convolutional network for multi-view learning

Author:

Xu ZhiyongORCID,Chen Weibin,Zou YingORCID,Fang Zihan,Wang ShipingORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference49 articles.

1. IGAGCN: Information geometry and attention-based spatiotemporal graph convolutional networks for traffic flow prediction;An;Neural Networks,2021

2. Multi-view graph convolutional networks with differentiable node selection;Chen;ACM Transactions on Knowledge Discovery from Data,2023

3. Learnable graph convolutional network and feature fusion for multi-view learning;Chen;Information Fusion,2023

4. Chen, M., Wei, Z., Huang, Z., Ding, B., & Li, Y. (2020). Simple and deep graph convolutional networks. In Proceedings of the international conference on machine learning (pp. 1725–1735).

5. Representation learning meets optimization-derived networks: From single-view to multi-view;Fang;IEEE Transactions on Multimedia,2024

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