Zobrazeno 1 - 10
of 861
pro vyhledávání: '"Chen, QingFeng"'
Unsupervised graph representation learning (UGRL) based on graph neural networks (GNNs), has received increasing attention owing to its efficacy in handling graph-structured data. However, existing UGRL methods ideally assume that the node features a
Externí odkaz:
http://arxiv.org/abs/2407.19944
The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention mechanism. In addition, increasing studies based on transformers have been
Externí odkaz:
http://arxiv.org/abs/2407.13205
Graph anomaly detection (GAD), which aims to identify abnormal nodes that differ from the majority within a graph, has garnered significant attention. However, current GAD methods necessitate training specific to each dataset, resulting in high train
Externí odkaz:
http://arxiv.org/abs/2405.16771
Publikováno v:
In Automation in Construction September 2024 165
Autor:
Zhang, Ying, Jiang, Fei, Li, Fengmin, Lu, Shaoyong, Liu, Zihao, Wang, Yuwen, Chi, Yiming, Jiang, Chenchen, Zhang, Ling, Chen, Qingfeng, He, Zhipeng, Zhao, Xiaoli, Qiao, Jianmin, Xu, Xiaoya, Leung, Kenneth Mei Yee, Liu, Xiaohui, Wu, Fengchang
Publikováno v:
In Journal of Hazardous Materials 15 July 2024 473
Publikováno v:
In Knowledge-Based Systems 12 May 2024 291
Autor:
Huang, Shuyang, Li, Qing, Qiu, Xiaohua, You, Hong, Lv, Ruimin, Liu, Wei, Chen, Qingfeng, Wang, Tiantian, Zhang, Jing, Ma, Junjian, Wang, Zihao, Ding, Shigang
Publikováno v:
In Continental Shelf Research April 2024 275
Autor:
Liu, Yixin, Pan, Shirui, Wang, Yu Guang, Xiong, Fei, Wang, Liang, Chen, Qingfeng, Lee, Vincent CS
Detecting anomalies for dynamic graphs has drawn increasing attention due to their wide applications in social networks, e-commerce, and cybersecurity. Recent deep learning-based approaches have shown promising results over shallow methods. However,
Externí odkaz:
http://arxiv.org/abs/2106.09876