Zobrazeno 1 - 10
of 84
pro vyhledávání: '"wang, Baokun"'
Autor:
Li, Jintang, Wei, Zheng, Dan, Jiawang, Zhou, Jing, Zhu, Yuchang, Wu, Ruofan, Wang, Baokun, Zhen, Zhang, Meng, Changhua, Jin, Hong, Zheng, Zibin, Chen, Liang
Real-world graphs are typically complex, exhibiting heterogeneity in the global structure, as well as strong heterophily within local neighborhoods. While a growing body of literature has revealed the limitations of common graph neural networks (GNNs
Externí odkaz:
http://arxiv.org/abs/2310.11664
Autor:
Dan, Jiawang, Wu, Ruofan, Liu, Yunpeng, Wang, Baokun, Meng, Changhua, Liu, Tengfei, Zhang, Tianyi, Wang, Ningtao, Fu, Xing, Li, Qi, Wang, Weiqiang
Graph representation learning has now become the de facto standard when handling graph-structured data, with the framework of message-passing graph neural networks (MPNN) being the most prevailing algorithmic tool. Despite its popularity, the family
Externí odkaz:
http://arxiv.org/abs/2310.11281
Autor:
Li, Jintang, Zhang, Huizhe, Wu, Ruofan, Zhu, Zulun, Wang, Baokun, Meng, Changhua, Zheng, Zibin, Chen, Liang
While contrastive self-supervised learning has become the de-facto learning paradigm for graph neural networks, the pursuit of higher task accuracy requires a larger hidden dimensionality to learn informative and discriminative full-precision represe
Externí odkaz:
http://arxiv.org/abs/2305.19306
Autor:
Tian, Sheng, Dong, Jihai, Li, Jintang, Zhao, Wenlong, Xu, Xiaolong, wang, Baokun, Song, Bowen, Meng, Changhua, Zhang, Tianyi, Chen, Liang
Anomaly detection aims to distinguish abnormal instances that deviate significantly from the majority of benign ones. As instances that appear in the real world are naturally connected and can be represented with graphs, graph neural networks become
Externí odkaz:
http://arxiv.org/abs/2305.13573
Autor:
Wu, Jiafu, Yao, Mufeng, Wu, Dong, Chi, Mingmin, Wang, Baokun, Wu, Ruofan, Fu, Xin, Meng, Changhua, Wang, Weiqiang
Graph representation plays an important role in the field of financial risk control, where the relationship among users can be constructed in a graph manner. In practical scenarios, the relationships between nodes in risk control tasks are bidirectio
Externí odkaz:
http://arxiv.org/abs/2303.03933
Autor:
Xue, Baiqiang, Jian, Xuemin, Peng, Lixia, Wu, Chuanhong, Fahira, Aamir, Syed, Ali Alamdar Shah, Xia, Disong, Wang, Baokun, Niu, Mingming, Jiang, Yajie, Ding, Yonghe, Gao, Chengwen, Zhao, Xiangzhong, Zhang, Qian, Shi, Yongyong, Li, Zhiqiang
Publikováno v:
In Sleep Medicine July 2024 119:201-209
Autor:
Chang, Kaihui, Jian, Xuemin, Wu, Chuanhong, Gao, Chengwen, Li, Yafang, Chen, Jianhua, Xue, Baiqiang, Ding, Yonghe, Peng, Lixia, Wang, Baokun, He, Lin, Xu, Yifeng, Li, Changgui, Li, Xingwang, Wang, Zhuo, Zhao, Xiangzhong, Pan, Dun, Yang, Qiangzhen, Zhou, Juan, Zhu, Zijia, Liu, Ze, Xia, Disong, Feng, Guoyin, Zhang, Qian, Wen, Yanqin, Shi, Yongyong, Li, Zhiqiang
Publikováno v:
In Biological Psychiatry June 2024
Autor:
Wang, Baokun, Ji, Renjie, Gong, Zheng, Zhao, Qingyang, Liu, Yonghong, Jin, Hui, Wang, Lixin, Xu, Zhiqian, Cai, Baoping, Ma, Jianmin
Publikováno v:
In Surface & Coatings Technology 15 May 2022 437
Autor:
Wang, Rongchun, Ren, Qingyu, Gao, Daili, Paudel, Yam Nath, Li, Xia, Wang, Lizhen, Zhang, Pengyu, Wang, Baokun, Shang, Xueliang, Jin, Meng
Publikováno v:
In Journal of Ethnopharmacology 10 May 2022 289
Autor:
JI, Renjie, ZHENG, Qian, LIU, Yonghong, JIN, Hui, ZHANG, Fan, LIU, Shenggui, WANG, Baokun, LU, Shuaichen, CAI, Baoping, LI, Xiaopeng
Publikováno v:
In Chinese Journal of Aeronautics March 2022 35(3):484-493