Zobrazeno 1 - 10
of 383
pro vyhledávání: '"Guan, Xinyu"'
Autor:
Zhang, Fanjin, Shi, Shijie, Zhu, Yifan, Chen, Bo, Cen, Yukuo, Yu, Jifan, Chen, Yelin, Wang, Lulu, Zhao, Qingfei, Cheng, Yuqing, Han, Tianyi, An, Yuwei, Zhang, Dan, Tam, Weng Lam, Cao, Kun, Pang, Yunhe, Guan, Xinyu, Yuan, Huihui, Song, Jian, Li, Xiaoyan, Dong, Yuxiao, Tang, Jie
Publikováno v:
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), August 25--29, 2024, Barcelona, Spain
With the rapid proliferation of scientific literature, versatile academic knowledge services increasingly rely on comprehensive academic graph mining. Despite the availability of public academic graphs, benchmarks, and datasets, these resources often
Externí odkaz:
http://arxiv.org/abs/2402.15810
Autor:
Qi, Ji, Yu, Jifan, Tu, Teng, Gao, Kunyu, Xu, Yifan, Guan, Xinyu, Wang, Xiaozhi, Dong, Yuxiao, Xu, Bin, Hou, Lei, Li, Juanzi, Tang, Jie, Guo, Weidong, Liu, Hui, Xu, Yu
Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i.e., long and informative commentary about the domain-specific scenes with appropriate reasoning) is s
Externí odkaz:
http://arxiv.org/abs/2303.14655
Source-Free Domain Adaptation (SFDA) aims to solve the domain adaptation problem by transferring the knowledge learned from a pre-trained source model to an unseen target domain. Most existing methods assign pseudo-labels to the target data by genera
Externí odkaz:
http://arxiv.org/abs/2210.07463
Autor:
Ling, Li-Li1 (AUTHOR), Guan, Xinyu1 (AUTHOR), Liu, Xiaoshuo2,3 (AUTHOR), Lei, Xiao-Mei1 (AUTHOR), Lin, Zhongyuan1 (AUTHOR), Jiang, Hai-Long1 (AUTHOR) jianglab@ustc.edu.cn
Publikováno v:
National Science Review. Jun2024, Vol. 11 Issue 6, p1-9. 9p.
Publikováno v:
In Applied Mathematics and Computation 15 May 2024 469
Autor:
Zou, Xu, Zheng, Qinkai, Dong, Yuxiao, Guan, Xinyu, Kharlamov, Evgeny, Lu, Jialiang, Tang, Jie
Graph Neural Networks (GNNs) have achieved promising performance in various real-world applications. However, recent studies have shown that GNNs are vulnerable to adversarial attacks. In this paper, we study a recently-introduced realistic attack sc
Externí odkaz:
http://arxiv.org/abs/2106.06663
Autor:
Tang, Sheng, Sun, Chuanchuan, He, Xintao, Gan, Wenhui, Wang, Linxiao, Qiao, Dan, Guan, Xinyu, Xu, Shan, Zheng, Pengwu, Zhu, Wufu
Publikováno v:
In European Journal of Medicinal Chemistry 5 January 2024 263
Autor:
Suleman, Suleman, Guan, Xinyu, Zhang, Yi, Waseem, Amir, Metin, Onder, Meng, Zheng, Jiang, Hai-Long
Publikováno v:
In Chemical Engineering Journal 15 November 2023 476
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.