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Data-driven rogue waves and parameters discovery in nearly integrable PT-symmetric Gross-Pitaevskii equations via PINNs deep learning 期刊论文
PHYSICA D-NONLINEAR PHENOMENA, 2022, 卷号: 439, 页码: 12
作者:  Zhong, Ming;  Gong, Shibo;  Tian, Shou-Fu;  Yan, Zhenya
收藏  |  浏览/下载：68/0  |  提交时间：2023/02/07
GeneralizedGrossPitaevskiiequation  ComplexPT-symmetricpotentials  Physics-informeddeepneuralnetworks  Data-driven rogue waves and parameters discovery discovery  
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  
DRVN (deep random vortex network): A new physics-informed machine learning method for simulating and inferring incompressible fluid flows 期刊论文
PHYSICS OF FLUIDS, 2022, 卷号: 34, 期号: 10, 页码: 21
作者:  Zhang, Rui;  Hu, Peiyan;  Meng, Qi;  Wang, Yue;  Zhu, Rongchan;  Chen, Bingguang;  Ma, Zhi-Ming;  Liu, Tie-Yan
收藏  |  浏览/下载：62/0  |  提交时间：2023/02/07
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：56/0  |  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  

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：126/0  |  提交时间：2023/02/07
Data -driven modeling  Normalizing flows  Uncertainty quantification  Random fields