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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：49/0  |  提交时间：2023/02/07
Physics -informed neural networks  Fractional Laplacian  Nonlocal operators  Uncertainty quantification  
Data-Driven Deep Learning for The Multi-Hump Solitons and Parameters Discovery in NLS Equations with Generalized PT-Scarf-II Potentials 期刊论文
NEURAL PROCESSING LETTERS, 2022, 页码: 19
作者:  Zhong, Ming;  Zhang, Jian-Guo;  Zhou, Zijian;  Tian, Shou-Fu;  Yan, Zhenya
收藏  |  浏览/下载：53/0  |  提交时间：2023/02/07
Focusing and defocusing nonlinear Schrodinger equations  Generalized PT-Scarf-II potential  Physics-informed deep neural networks  Data-driven solitons and parameters discovery  
Data-driven peakon and periodic peakon solutions and parameter discovery of some nonlinear dispersive equations via deep learning 期刊论文
PHYSICA D-NONLINEAR PHENOMENA, 2021, 卷号: 428, 页码: 15
作者:  Wang, Li;  Yan, Zhenya
收藏  |  浏览/下载：116/0  |  提交时间：2022/04/02
Nonlinear dispersive equation  Initial-boundary value conditions  Physics-informed neural networks  Deep learning  Data-driven peakon and periodic peakon  solutions Data-driven parameter discovery  
Data-driven rogue waves and parameter discovery in the defocusing nonlinear Schrodinger equation with a potential using the PINN deep learning 期刊论文
PHYSICS LETTERS A, 2021, 卷号: 404, 页码: 7
作者:  Wang, Li;  Yan, Zhenya
收藏  |  浏览/下载：124/0  |  提交时间：2021/10/26
Defocusing NLS equation with the  time-dependent potential  Initial-boundary value conditions  Physics-informed neural networks  Deep learning  Data-driven rogue waves and parameter discovery  
Solving forward and inverse problems of the logarithmic nonlinear Schrodinger equation with PT-symmetric harmonic potential via deep learning 期刊论文
PHYSICS LETTERS A, 2021, 卷号: 387, 页码: 12
作者:  Zhou, Zijian;  Yan, Zhenya
收藏  |  浏览/下载：143/0  |  提交时间：2021/04/26
Logarithmic nonlinear Schrodinger equation  PT-symmetric potentials  Physics-informed neural networks  Deep learning  Data-driven discovery of LNLS equation  Data-driven solitons  
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems 期刊论文
NEURAL NETWORKS, 2020, 卷号: 132, 页码: 166-179
作者:  Jin, Pengzhan;  Zhang, Zhen;  Zhu, Aiqing;  Tang, Yifa;  Karniadakis, George Em
收藏  |  浏览/下载：143/0  |  提交时间：2021/04/26
Deep learning  Physics-informed  Dynamical systems  Hamiltonian systems  Symplectic maps  Symplectic integrators