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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：51/0  |  提交时间：2023/02/07
Physics -informed neural networks  Fractional Laplacian  Nonlocal operators  Uncertainty quantification  

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：124/0  |  提交时间：2023/02/07
Data -driven modeling  Normalizing flows  Uncertainty quantification  Random fields  
Stein variational gradient descent with local approximations 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 卷号: 386, 页码: 20
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：103/0  |  提交时间：2022/04/02
Stein variational gradient decent  Bayesian inference  Deep learning  Local approximation  
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：139/0  |  提交时间：2021/04/26
Kernel interpolation  Fekete points  Cholesky decomposition with pivoting  Hermite interpolation  Uncertainty quantification  
AN EXPLICIT MULTISTEP SCHEME FOR MEAN-FIELD FORWARD-BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS 期刊论文
JOURNAL OF COMPUTATIONAL MATHEMATICS, 2021, 页码: 25
作者:  Sun, Yabing;  Yang, Jie;  Zhao, Weidong;  Zhou, Tao
收藏  |  浏览/下载：112/0  |  提交时间：2022/04/02
Mean-field forward backward stochastic differential equations  Explicit multistep scheme  Error estimates  
AN ACCELERATION STRATEGY FOR RANDOMIZE-THEN-OPTIMIZE SAMPLING VIA DEEP NEURAL NETWORKS* 期刊论文
JOURNAL OF COMPUTATIONAL MATHEMATICS, 2021, 卷号: 39, 期号: 6, 页码: 848-864
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：124/0  |  提交时间：2022/04/02
Bayesian inverse problems  Deep neural network  Markov chain Monte Carlo  
AN ENERGY STABLE AND MAXIMUM BOUND PRESERVING SCHEME WITH VARIABLE TIME STEPS FOR TIME FRACTIONAL ALLEN--CAHN EQUATION 期刊论文
SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2021, 卷号: 43, 期号: 5, 页码: A3503-A3526
作者:  Liao, Hong-lin;  Tang, Tao;  Zhou, Tao
收藏  |  浏览/下载：87/0  |  提交时间：2022/04/02
time-fractional Allen--Cahn equation  asymptotic preserving  energy stability  adaptive time stepping  max-imum principle  
Diagonalization-based parallel-in-time algorithms for parabolic PDE-constrained optimization problems 期刊论文
ESAIM-CONTROL OPTIMISATION AND CALCULUS OF VARIATIONS, 2020, 卷号: 26, 页码: 26
作者:  Wu, Shu-Lin;  Zhou, Tao
收藏  |  浏览/下载：149/0  |  提交时间：2021/04/26
Parabolic PDE-constrained optimization  PinT algorithm  diagonalization technique  preconditioner  GMRES  BiCGStab  
An Adaptive Surrogate Modeling Based on Deep Neural Networks for Large-Scale Bayesian Inverse Problems 期刊论文
COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2020, 卷号: 28, 期号: 5, 页码: 2180-2205
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：134/0  |  提交时间：2021/01/14
Bayesian inverse problems  deep neural networks  multi-fidelity surrogate modeling  Markov chain Monte Carlo  
A second-order and nonuniform time-stepping maximum-principle preserving scheme for time-fractional Allen-Cahn equations 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2020, 卷号: 414, 页码: 16
作者:  Liao, Hong-lin;  Tang, Tao;  Zhou, Tao
收藏  |  浏览/下载：165/0  |  提交时间：2020/06/30
Time-fractional Allen-Cahn equation  Alikhanov formula  Adaptive time-stepping strategy  Discrete maximum principle  Sharp error estimate