Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Su, Wanhua"'
Partial Differential Equations (PDEs) model various physical phenomena, such as electromagnetic fields and fluid mechanics. Methods like Sparse Identification of Nonlinear Dynamics (SINDy) and PDE-Net 2.0 have been developed to identify and model PDE
Externí odkaz:
http://arxiv.org/abs/2410.18110
We propose a heralded nonlocal protocol for implementing an entangling gate on two stationary qubits coupled to spatially separated cavities. By dynamically controlling the evolution of the composite system, the entangling gate can be achieved withou
Externí odkaz:
http://arxiv.org/abs/2305.00642
Autor:
Zhang, Min1 (AUTHOR) zhangminmrzr@163.com, Su, Wanhua1 (AUTHOR) 2019201376@tju.edu, Jia, Zhi1 (AUTHOR)
Publikováno v:
Energies (19961073). Sep2024, Vol. 17 Issue 17, p4351. 21p.
Autor:
Liu, Yize1 (AUTHOR) liuyize@tju.edu.cn, Su, Wanhua1 (AUTHOR)
Publikováno v:
Energies (19961073). Jun2024, Vol. 17 Issue 11, p2549. 27p.
Autor:
Liu, Yize1 (AUTHOR) liuyize@tju.edu.cn, Su, Wanhua1 (AUTHOR) whsu@tju.edu.cn, Wu, Binyang1 (AUTHOR), Wang, Jiayong1 (AUTHOR)
Publikováno v:
Energies (19961073). Mar2024, Vol. 17 Issue 5, p1065. 24p.
Publikováno v:
In Fuel 1 December 2021 305
Autor:
Gu, Wenyu1 (AUTHOR) guwenyu@tju.edu.cn, Su, Wanhua1 (AUTHOR) whsu@tju.edu.cn
Publikováno v:
Energies (19961073). Aug2023, Vol. 16 Issue 16, p6008. 20p.
Autor:
Su, Wanhua
This research is motivated by a drug discovery problem -- the AIDS anti-viral database from the National Cancer Institute. The objective of the study is to develop effective statistical methods to model the relationship between the chemical structure
Externí odkaz:
http://hdl.handle.net/10012/3598
When evaluating medical tests or biomarkers for disease classification, the area under the receiver-operating characteristic (ROC) curve is a widely used performance metric that does not require us to commit to a specific decision threshold. For the
Externí odkaz:
http://arxiv.org/abs/1310.5103
When using the K-nearest neighbors method, one often ignores uncertainty in the choice of K. To account for such uncertainty, Holmes and Adams (2002) proposed a Bayesian framework for K-nearest neighbors (KNN). Their Bayesian KNN (BKNN) approach uses
Externí odkaz:
http://arxiv.org/abs/0804.1325