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Monte Carlo fPINNs: Deep learning method for forward and inverse problems involving high dimensional fractional partial differential equations 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 卷号: 400, 页码: 17
作者:  Guo, Ling;  Wu, Hao;  Yu, Xiaochen;  Zhou, Tao
收藏  |  浏览/下载：50/0  |  提交时间：2023/02/07
Physics -informed neural networks  Fractional Laplacian  Nonlocal operators  Uncertainty quantification  
A spectral method for stochastic fractional PDEs using dynamically-orthogonal/bi-orthogonal decomposition 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 卷号: 461, 页码: 17
作者:  Zhao, Yue;  Mao, Zhiping;  Guo, Ling;  Tang, Yifa;  Karniadakis, George Em
收藏  |  浏览/下载：59/0  |  提交时间：2023/02/07
Uncertainty quantification  Anomalous transport  Quasi Monte Carlo simulation  Generalized polynomial chaos  Long-time integration  Poly-fractonomials  

Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models

 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 卷号: 461, 页码: 18
作者:  Guo, Ling;  Wu, Hao;  Zhou, Tao
收藏  |  浏览/下载：119/0  |  提交时间：2023/02/07
Data -driven modeling  Normalizing flows  Uncertainty quantification  Random fields  
Optimal design for kernel interpolation: Applications to uncertainty quantification 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2021, 卷号: 430, 页码: 19
作者:  Narayan, Akil;  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：138/0  |  提交时间：2021/04/26
Kernel interpolation  Fekete points  Cholesky decomposition with pivoting  Hermite interpolation  Uncertainty quantification  
Quantum states as observables: Their variance and nonclassicality 期刊论文
PHYSICAL REVIEW A, 2020, 卷号: 102, 期号: 6, 页码: 6
作者:  Zhang, Yue;  Luo, Shunlong
收藏  |  浏览/下载：147/0  |  提交时间：2021/04/26
Quantifying non-Gaussianity of bosonic fields via an uncertainty relation 期刊论文
PHYSICAL REVIEW A, 2020, 卷号: 101, 期号: 1, 页码: 8
作者:  Fu, Shuangshuang;  Luo, Shunlong;  Zhang, Yue
收藏  |  浏览/下载：170/0  |  提交时间：2020/05/24