1 code implementation • 31 Dec 2022 • Xingping Xian, Tao Wu, Xiaoke Ma, Shaojie Qiao, Yabin Shao, Chao Wang, Lin Yuan, Yu Wu
Instead of sampling positive and negative links and heuristically computing the features of their enclosing subgraphs, GraphLP utilizes the feature learning ability of deep-learning models to automatically extract the structural patterns of graphs for link prediction under the assumption that real-world graphs are not locally isolated.
no code implementations • 20 May 2018 • Tao Wu, Shaojie Qiao, Xingping Xian, Xi-Zhao Wang, Wei Wang, Yanbing Liu
In addition, the model is capable of measuring the importance of microscopic network elements, i. e., nodes and links, in terms of network regularity thereby allowing us to regulate the reconstructability of networks based on them.