Zobrazeno 1 - 10
of 540
pro vyhledávání: '"Wu Hulin"'
Deep residual networks (ResNets) have shown state-of-the-art performance in various real-world applications. Recently, the ResNets model was reparameterized and interpreted as solutions to a continuous ordinary differential equation or Neural-ODE mod
Externí odkaz:
http://arxiv.org/abs/2209.10633
Publikováno v:
In Natural Language Processing Journal September 2024 8
Autor:
Jiang, Yongqiang, Wu, Mingxin, Li, Tingle, Wang, Qi, Song, Sunny, Wu, Hulin, Huang, Junchen, Yang, Songtao, Sun, Changyu, Wang, Shuzeng
Publikováno v:
In Fuel 1 September 2024 371 Part B
Autor:
Zha, Alicia, Zhang, Chenguang, Zhu, Gen, Huang, Xinran, Anjum, Sahar, Talebi, Yashar, Savitz, Sean, Wu, Hulin
Publikováno v:
In Journal of Stroke and Cerebrovascular Diseases August 2024 33(8)
Autor:
Fraser, Stuart, Levy, Samantha M., Moreno, Amee, Zhu, Gen, Savitz, Sean, Zha, Alicia, Wu, Hulin
Publikováno v:
In Heliyon 30 May 2024 10(10)
Autor:
Kawi, Jennifer, Yeh, Chao Hsing, Grant, Lauren, Huang, Xinran, Wu, Hulin, Hua, Chunyan, Christo, Paul
Publikováno v:
In Complementary Therapies in Medicine May 2024 81
Ordinary differential equations (ODEs) are widely used to model dynamical behavior of systems. It is important to perform identifiability analysis prior to estimating unknown parameters in ODEs (a.k.a. inverse problem), because if a system is unident
Externí odkaz:
http://arxiv.org/abs/2103.05660
Publikováno v:
BMC Bioinformatics, Vol 11, Iss 1, p 261 (2010)
Abstract Background The replication rate (or fitness) between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance.
Externí odkaz:
https://doaj.org/article/10c19331b8f34a14be03846e9a590775