Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Ruosi Wan"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Time-stamped cross-sectional data, which lack linkage across time points, are commonly generated in single-cell transcriptional profiling. Many previous methods for inferring gene regulatory networks (GRNs) driving cell-state transitions rel
Externí odkaz:
https://doaj.org/article/0e35915315fe4df4a6ed42e569362c06
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 16:1-25
Regularization that incorporates the linear combination of empirical loss and explicit regularization terms as the loss function has been frequently used for many machine learning tasks. The explicit regularization term is designed in different types
Autor:
Ruosi Wan, Xiaoliang Sunney Xie, Y Zhang, Ge Gao, Fuchou Tang, Jia J, Feng Tian, Hao Ge, Yong Peng
Nowadays the advanced technology for single-cell transcriptional profiling enables people to routinely generate thousands of single-cell expression data, in which data from different cell states or time points are derived from different samples. With
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cb5e5e2ba43a6e0c637bd0d742406d1
https://doi.org/10.1101/2021.05.12.443928
https://doi.org/10.1101/2021.05.12.443928
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030461461
ECML/PKDD (2)
ECML/PKDD (2)
In statistics and machine learning, approximation of an intractable integration is often achieved by using the unbiased Monte Carlo estimator, but the variances of the estimation are generally high in many applications. Control variates approaches ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68c60ddea9d00b9788d85934648927b8
https://doi.org/10.1007/978-3-030-46147-8_32
https://doi.org/10.1007/978-3-030-46147-8_32
Autor:
Liang Yuding, Ruosi Wan, Jian Sun, Yichen Wei, Yiming Hu, Qingyi Gu, Zichao Guo, Xiangyu Zhang
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585280
ECCV (19)
ECCV (19)
In this work, we present a simple and general search space shrinking method, called Angle-Based search space Shrinking (ABS), for Neural Architecture Search (NAS). Our approach progressively simplifies the original search space by dropping unpromisin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0cc306fc7b386199cad6cbb5ace5b47
https://doi.org/10.1007/978-3-030-58529-7_8
https://doi.org/10.1007/978-3-030-58529-7_8
Publikováno v:
ICDM
Transfer learning have been frequently used to improve deep neural network training through incorporating weights of pre-trained networks as the starting-point of optimization for regularization. While deep transfer learning can usually boost the per
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d245f961ceca9700678743a1e40b1820
http://arxiv.org/abs/1911.07489
http://arxiv.org/abs/1911.07489
Publikováno v:
Ecological Indicators, Vol 154, Iss , Pp 110605- (2023)
A program of ecological compensation (EC) is an effective means to solve the potential unfairness caused by the difference in environmental quality between the upper, middle, and lower reaches of river basins, alleviate the conflict of economic inter
Externí odkaz:
https://doaj.org/article/1f16c43b42de461d8e81e817f0c3cccb
Publikováno v:
Materials, Vol 15, Iss 16, p 5647 (2022)
Synchrotron radiation dynamic imaging technology combined with the static characterization method was used to study the microstructural evolution and the growth kinetics of intermetallic compounds (IMCs) at the liquid Al/solid Cu interface. The resul
Externí odkaz:
https://doaj.org/article/eb53b317634c406c87d3ff5291f508bf
Autor:
Chunbo Xiu, Ruosi Wang
Publikováno v:
IEEE Access, Vol 6, Pp 33819-33825 (2018)
In order to improve the control performance of the transport vehicle, the dynamic model, instead of the kinematic model, is established. The equation of state can be divided into two independent subsystems: the speed sub system and the attitude angle
Externí odkaz:
https://doaj.org/article/ed73863df3a642ea80f8838f43ef5239
Autor:
Xiang-Zhen Kong, Zonglei Zhen, Xueting Li, Huan-Hua Lu, Ruosi Wang, Ling Liu, Yong He, Yufeng Zang, Jia Liu
Publikováno v:
PLoS ONE, Vol 9, Iss 8, p e104989 (2014)
Magnetic resonance imaging (MRI) provides valuable data for understanding the human mind and brain disorders, but in-scanner head motion introduces systematic and spurious biases. For example, differences in MRI measures (e.g., network strength, whit
Externí odkaz:
https://doaj.org/article/f9386c07cce543b0a0079f93bca4ed3e