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pro vyhledávání: '"Hou, Bitan"'
Autor:
Chen, Jianpeng, Wang, Yujing, Zeng, Ming, Xiang, Zongyi, Hou, Bitan, Tong, Yunhai, J. Mengshoel, Ole, Ren, Yazhou
Publikováno v:
In Information Sciences July 2024 674
Autor:
Chen, Jianpeng, Wang, Yujing, Zeng, Ming, Xiang, Zongyi, Hou, Bitan, Tong, Yunhai, Mengshoel, Ole J., Ren, Yazhou
Graph Neural Networks (GNNs) have been extensively used for mining graph-structured data with impressive performance. However, because these traditional GNNs do not distinguish among various downstream tasks, embeddings embedded by them are not alway
Externí odkaz:
http://arxiv.org/abs/2106.10866
Autor:
Hou, Bitan, Wang, Yujing, Zeng, Ming, Jiang, Shan, Mengshoel, Ole J., Tong, Yunhai, Bai, Jing
Graph is a natural representation of data for a variety of real-word applications, such as knowledge graph mining, social network analysis and biological network comparison. For these applications, graph embedding is crucial as it provides vector rep
Externí odkaz:
http://arxiv.org/abs/1911.09454