Zobrazeno 1 - 10
of 2 355
pro vyhledávání: '"Li Danyang"'
Autor:
Zhou, Shuying, Sun, Mouyuan, Feng, Hai-Cheng, Li, Sha-Sha, Xue, Yongquan, Wang, Jun-Xian, Cai, Zhen-Yi, Bai, Jin-Ming, Li, Danyang, Guo, Hengxiao, Liu, H. T., Lu, Kai-Xing, Mao, Jirong, Marculewicz, Marcin, Wang, Jian-Guo
Resolving the inner structures of active galactic nuclei (AGNs) provides the "standard ruler" to measure the parallax distances of the Universe and a powerful way to weigh supermassive black holes (SMBHs). Thanks to time-domain observations, it is po
Externí odkaz:
http://arxiv.org/abs/2408.11292
There has been a growing interest in extracting formal descriptions of the system behaviors from data. Signal Temporal Logic (STL) is an expressive formal language used to describe spatial-temporal properties with interpretability. This paper introdu
Externí odkaz:
http://arxiv.org/abs/2405.06670
Single-photon terahertz (THz) detection is one of the most demanding technology for a variety of fields and could lead to many breakthroughs. Although its significant progress has been made in the last two decades, operating it at room temperature st
Externí odkaz:
http://arxiv.org/abs/2403.05833
Autor:
Hong, Sirui, Lin, Yizhang, Liu, Bang, Liu, Bangbang, Wu, Binhao, Zhang, Ceyao, Wei, Chenxing, Li, Danyang, Chen, Jiaqi, Zhang, Jiayi, Wang, Jinlin, Zhang, Li, Zhang, Lingyao, Yang, Min, Zhuge, Mingchen, Guo, Taicheng, Zhou, Tuo, Tao, Wei, Tang, Xiangru, Lu, Xiangtao, Zheng, Xiawu, Liang, Xinbing, Fei, Yaying, Cheng, Yuheng, Gou, Zhibin, Xu, Zongze, Wu, Chenglin
Large Language Model (LLM)-based agents have shown effectiveness across many applications. However, their use in data science scenarios requiring solving long-term interconnected tasks, dynamic data adjustments and domain expertise remains challengin
Externí odkaz:
http://arxiv.org/abs/2402.18679
Autor:
Li, Danyang, Tron, Roberto
Time-series data can represent the behaviors of autonomous systems, such as drones and self-driving cars. The task of binary and multi-class classification for time-series data has become a prominent area of research. Neural networks represent a popu
Externí odkaz:
http://arxiv.org/abs/2402.12397
Imitation learning methods have demonstrated considerable success in teaching autonomous systems complex tasks through expert demonstrations. However, a limitation of these methods is their lack of interpretability, particularly in understanding the
Externí odkaz:
http://arxiv.org/abs/2402.10310
We use LCOGT observations (MJD $59434-59600$) with a total exposure time of $\simeq 50$ hours and a median cadence of $0.5$ days to measure the inter-band time delays (with respect to $u$) in the $g$, $r$, and $i$ continua of a highly variable AGN, 6
Externí odkaz:
http://arxiv.org/abs/2401.12524
Knowledge distillation is one of the methods for model compression, and existing knowledge distillation techniques focus on how to improve the distillation algorithm so as to enhance the distillation efficdiency. This paper introduces dynamic increme
Externí odkaz:
http://arxiv.org/abs/2311.13811
Autor:
Li, Lifang1 (AUTHOR), Li, Danyang1 (AUTHOR), Jin, Jingnan1 (AUTHOR), Xu, Fanfan1 (AUTHOR), He, Ni1 (AUTHOR), Ren, Yingjie1 (AUTHOR), Wang, Xiaokun1 (AUTHOR), Tian, Liting1 (AUTHOR), Chen, Biying1 (AUTHOR), Li, Xiaoju1 (AUTHOR), Chen, Zihong1 (AUTHOR), Zhang, Lanxin1 (AUTHOR), Qiao, Lukuan1 (AUTHOR), Wang, Lihua1 (AUTHOR) wanglh211@163.com, Wang, Jianjian1 (AUTHOR) wangjian_427@163.com
Publikováno v:
Journal of Neuroinflammation. 8/7/2024, Vol. 21 Issue 1, p1-17. 17p.
Autor:
Zhao, Yuzhou1 (AUTHOR), Li, Danyang2 (AUTHOR), Zhuang, Jing1 (AUTHOR), Li, Zhimeng1 (AUTHOR), Xia, Qingxin3 (AUTHOR), Li, Zhi1 (AUTHOR), Yu, Juan4 (AUTHOR), Wang, Jinbang1 (AUTHOR), Zhang, Yong5 (AUTHOR), Li, Ke2 (AUTHOR), Xu, Shuning2 (AUTHOR), Li, Sen1 (AUTHOR), Ma, Pengfei1 (AUTHOR), Cao, Yanghui1 (AUTHOR), Liu, Chenyu1 (AUTHOR), Xu, Chunmiao6 (AUTHOR), Liu, Zhentian7 (AUTHOR), Wei, Jinwang8 (AUTHOR), Zhang, Chengjuan3 (AUTHOR), Qiao, Lei2 (AUTHOR)
Publikováno v:
Clinical & Translational Medicine. May2024, Vol. 14 Issue 5, p1-19. 19p.