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AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding

Network embedding represents nodes in a continuous vector space and preserves structure information from the Network. Existing methods usually adopt a “one-size-fits-all” approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different scales play different roles in the embedding learning.

Data and Resources

Cite this as

Lei Sang, Min Xu, Shengsheng Qian, Xindong Wu (2024). Dataset: AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding. https://doi.org/10.57702/0ldsfq5z

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.1803.09080
Author Lei Sang
More Authors
Min Xu
Shengsheng Qian
Xindong Wu