Zobrazeno 1 - 10
of 183
pro vyhledávání: '"Wang, Hongqiao"'
Identifying dynamical system (DS) is a vital task in science and engineering. Traditional methods require numerous calls to the DS solver, rendering likelihood-based or least-squares inference frameworks impractical. For efficient parameter inference
Externí odkaz:
http://arxiv.org/abs/2409.11745
Deep learning method is of great importance in solving partial differential equations. In this paper, inspired by the failure-informed idea proposed by Gao et.al. (SIAM Journal on Scientific Computing 45(4)(2023)) and as an improvement, a new accurat
Externí odkaz:
http://arxiv.org/abs/2404.18838
Stochastic Differential Equations (SDEs) serve as a powerful modeling tool in various scientific domains, including systems science, engineering, and ecological science. While the specific form of SDEs is typically known for a given problem, certain
Externí odkaz:
http://arxiv.org/abs/2401.02529
Physics-guided deep learning is an important prevalent research topic in scientific machine learning, which has tremendous potential in various complex applications including science and engineering. In these applications, data is expensive to acquir
Externí odkaz:
http://arxiv.org/abs/2312.12693
Failure probability estimation problem is an crucial task in engineering. In this work we consider this problem in the situation that the underlying computer models are extremely expensive, which often arises in the practice, and in this setting, red
Externí odkaz:
http://arxiv.org/abs/2302.06837
Autor:
Wang, Hongqiao1 (AUTHOR) whq@nwpu.edu.cn, Yu, Guoqing2 (AUTHOR) yuguoqing@mail.nwpu.edu.cn, Cheng, Jinyu3 (AUTHOR) l_z_dect@mail.nwpu.edu.cn, Zhang, Zhaoxiang1 (AUTHOR) wangxuan@nwpu.edu.cn, Wang, Xuan1 (AUTHOR) xuyuelei@nwpu.edu.cn, Xu, Yuelei1 (AUTHOR)
Publikováno v:
Remote Sensing. Oct2024, Vol. 16 Issue 20, p3782. 17p.
Publikováno v:
In Journal of Computational Physics 15 June 2024 507
The saddle point (SP) calculation is a grand challenge for computationally intensive energy function in computational chemistry area, where the saddle point may represent the transition state (TS). The traditional methods need to evaluate the gradien
Externí odkaz:
http://arxiv.org/abs/2108.04698
In this work we consider Bayesian inference problems with intractable likelihood functions. We present a method to compute an approximate of the posterior with a limited number of model simulations. The method features an inverse Gaussian Process reg
Externí odkaz:
http://arxiv.org/abs/2102.10583
Publikováno v:
In European Journal of Surgical Oncology January 2024 50(1)