Zobrazeno 1 - 10
of 185
pro vyhledávání: '"Wei, Zhicheng"'
Autor:
He, Bingyang, Yan, Zhiqiao, Liu, Tingwei, Wei, Zhicheng, Yan, Qiusheng, Chen, Zhijun, Pan, Jisheng, Liu, Zhengyang, Wang, Juan, Chen, Feng
Publikováno v:
In Journal of Materials Research and Technology September-October 2024 32:2063-2075
Autor:
Wei, Zhicheng, Shao, Qianqi, Yuan, Yujie, Jin, Hongqi, Cao, Jiashun, Liu, Weijing, Zhao, Gang, Luo, Jingyang
Publikováno v:
In Process Safety and Environmental Protection September 2024 189:146-153
Autor:
Fu, Wentao, Li, Yaohua, Halik, Ümüt, Tian, Aolei, Ainiwaer, Ailiya, Liu, Yuying, Wei, Zhicheng, Shi, Lei, Welp, Martin
Publikováno v:
In Building and Environment 1 January 2025 267 Part A
Autor:
Liu, Tingwei, Yan, Zhiqiao, He, Bingyang, Liu, Yong, Liu, Bin, Wei, Zhicheng, Chen, Feng, Long, Ying
Publikováno v:
In Tribology International January 2025 201
Autor:
Wei, ZhiCheng1 (AUTHOR), Tian, Ling2 (AUTHOR), Xu, Huajun1 (AUTHOR), Li, Chenyang1 (AUTHOR), Wu, Kejia1 (AUTHOR), Zhu, Huaming1 (AUTHOR), Guan, Jian1 (AUTHOR), Yu, Yafeng3 (AUTHOR) yfyu1024@163.com, Qian, Di4 (AUTHOR) skeayqd@sina.com, Li, Xinyi1 (AUTHOR) lixinyilixinyi123@163.com
Publikováno v:
Nutrition & Metabolism. 7/2/2024, Vol. 21 Issue 1, p1-9. 9p.
Autor:
Cheng, Xiaoshi, Wei, Zhicheng, Cao, Wangbei, Feng, Qian, Liu, Jianchao, Wu, Yang, Feng, Leiyu, Wang, Dongbo, Luo, Jingyang
Publikováno v:
In Water Research 15 August 2024 260
Autor:
Liu, Xinyi, Guo, Wen, Cheng, Xiaoshi, Wei, Zhicheng, Feng, Qian, Cheng, Song, Zhang, Qin, Luo, Jingyang
Publikováno v:
In Journal of Hazardous Materials 15 August 2024 475
Autor:
Zhang, Wenkai, Lin, Hongyu, Han, Xianpei, Sun, Le, Liu, Huidan, Wei, Zhicheng, Yuan, Nicholas Jing
Denoising is the essential step for distant supervision based named entity recognition. Previous denoising methods are mostly based on instance-level confidence statistics, which ignore the variety of the underlying noise distribution on different da
Externí odkaz:
http://arxiv.org/abs/2106.09234
This paper studies how to automatically generate a natural language text that describes the facts in knowledge graph (KG). Considering the few-shot setting, we leverage the excellent capacities of pretrained language models (PLMs) in language underst
Externí odkaz:
http://arxiv.org/abs/2106.01623
Publikováno v:
In Journal of Materials Research and Technology May-June 2024 30:3394-3405