Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Xufang Luo"'
Autor:
Junyi Yan, Xufang Luo, Jiahang Xu, Dongsheng Li, Lili Qiu, Dianyou Li, Peng Cao, Chencheng Zhang
Publikováno v:
Insights into Imaging, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Background The efficacy of levodopa, the most crucial metric for Parkinson’s disease diagnosis and treatment, is traditionally gauged through the levodopa challenge test, which lacks a predictive model. This study aims to probe the predict
Externí odkaz:
https://doaj.org/article/ac123a623eff4ee2a9559a75c456fece
Autor:
Wenmin Wang, Jizheng Wang, Ke Yao, Shuiyun Wang, Meng Nie, Yizi Zhao, Bohong Wang, Huanhuan Pang, Jingjing Xu, Guixin Wu, Minjie Lu, Nan Tang, Chunmei Qi, Hengzhi Pei, Xufang Luo, Dongsheng Li, Tianshu Yang, Qing Sun, Xiang Wei, Yan Li, Dingsheng Jiang, Peng Li, Lei Song, Zeping Hu
Publikováno v:
Nature Cardiovascular Research. 1:445-461
Publikováno v:
Proceedings of the ACM Web Conference 2022.
Publikováno v:
Proceedings of the ACM Web Conference 2022.
Publikováno v:
International Journal of Genomics, Vol 2016 (2016)
Purpose. To decipher transcriptomic changes and related genes with potential functions against Bombyx mori nucleopolyhedrovirus infection and to increase the understanding of the enhanced virus resistance of silkworm on the transcriptomic level. Meth
Externí odkaz:
https://doaj.org/article/7e47451e43774f6695a182ab4059b457
Autor:
Xufang Luo, Yunhong Wang
Publikováno v:
Neurocomputing. 403:109-120
In recent years, aided by deep neural networks (DNNs), reinforcement learning (RL) algorithms have been achieving great success in more and more tasks. In general, model-free RL algorithms are widely applicable, but sometimes suffer from low sample e
Autor:
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
It is challenging for reinforcement learning (RL) algorithms to succeed in real-world applications like financial trading and logistic system due to the noisy observation and environment shifting between training and evaluation. Thus, it requires bot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9b33f047c46838cd979b95647981eaa
Autor:
Cong Yin, Zewei Ma, Fan Li, Kelin Yang, Tao Wang, Lina Wang, Xiaotong Zhu, Songbo Wang, Ping Gao, Qianyun Xi, Yongliang Zhang, Xufang Luo, Yuelin Deng, Gang Shu, Qingyan Jiang
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
IJCAI
Learning expressive representations is always crucial for well-performed policies in deep reinforcement learning (DRL). Different from supervised learning, in DRL, accurate targets are not always available, and some inputs with different actions only
Publikováno v:
Neural Information Processing ISBN: 9783030367077
ICONIP (1)
ICONIP (1)
Nowadays, the research for learning representations with deep neural networks (DNNs) is attracting more and more attentions. In general, most of studies focus on designing principles for learning representations when the learning model is stochastic,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b47d4464730be13561f69e503152890
https://doi.org/10.1007/978-3-030-36708-4_21
https://doi.org/10.1007/978-3-030-36708-4_21