Zobrazeno 1 - 10
of 1 986
pro vyhledávání: '"Cao, Fang"'
Autor:
Wantlin, Kathryn, Wu, Chenwei, Huang, Shih-Cheng, Banerjee, Oishi, Dadabhoy, Farah, Mehta, Veeral Vipin, Han, Ryan Wonhee, Cao, Fang, Narayan, Raja R., Colak, Errol, Adamson, Adewole, Heacock, Laura, Tison, Geoffrey H., Tamkin, Alex, Rajpurkar, Pranav
Medical data poses a daunting challenge for AI algorithms: it exists in many different modalities, experiences frequent distribution shifts, and suffers from a scarcity of examples and labels. Recent advances, including transformers and self-supervis
Externí odkaz:
http://arxiv.org/abs/2304.08486
Autor:
Cao Fang, Chang Xu, Wei Zhang, Meng Zhou, Dong Tan, Lixia Qian, Daqiao Hu, Shan Jin, Manzhou Zhu
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Dual emission (DE) in nanoclusters (NCs) is considerably significant in the research and application of ratiometric sensing, bioimaging, and novel optoelectronic devices. Exploring the DE mechanism in open-shell NCs with doublet or quartet e
Externí odkaz:
https://doaj.org/article/137f9cf7b25249cb9c9e6bce3da1f9e7
Autor:
Xu, Liping1 (AUTHOR), Cao, Fang2,3 (AUTHOR), Wang, Lian2 (AUTHOR), Liu, Weihua2 (AUTHOR), Gao, Meizhu2 (AUTHOR), Zhang, Li2 (AUTHOR), Hong, Fuyuan2 (AUTHOR) Hongdoc@aliyun.com, Lin, Miao2 (AUTHOR) mlinys@hotmail.com
Publikováno v:
Renal Failure. Dec2024, Vol. 46 Issue 2, p1-10. 10p.
Publikováno v:
In Signal Processing October 2024 223
Autor:
Xu, Jun, Cao, Fang, Yang, Xiaoyuan, Chen, Xing, Zhang, Yan, Chen, Junwei, He, Liqing, Kang, Wenpei
Publikováno v:
In Journal of Colloid And Interface Science September 2024 669:825-834
Autor:
VARSHNEY, ANUBODH S., CALMA, JAMIE, KALWANI, NEIL M., HSIAO, STEPHANIE, SALLAM, KARIM, CAO, FANG, DIN, NATASHA, SCHIRMER, JESSICA, BHATT, ANKEET S., AMBROSY, ANDREW P., HEIDENREICH, PAUL, SANDHU, ALEXANDER T.
Publikováno v:
In Journal of Cardiac Failure September 2024 30(9):1086-1095
Publikováno v:
In Materials Science & Engineering A August 2024 908
Publikováno v:
In Chemical Physics 1 January 2025 588
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 1, Pp 111-126 (2024)
For computing-intensive artificial intelligence (AI) training tasks, the computational graph is more complex, and data loading, task division of the computational graph, and load balancing of task scheduling have become the key factors affecting the
Externí odkaz:
https://doaj.org/article/745e0537fcd04fd78f65f5f59263d8a7