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Deep learning neural networks for the third-order nonlinear Schrodinger equation: Solitons, breathers, and rogue waves

Deep learning neural networks for the third-order nonlinear Schrodinger equation: Solitons, breathers, and rogue waves

Zijian Zhou
Zhenya Yan
ArXivPDFHTML

Papers citing "Deep learning neural networks for the third-order nonlinear Schrodinger equation: Solitons, breathers, and rogue waves"

3 / 3 papers shown
Title
Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning
Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning
Li Wang
Zhenya Yan
43
81
0
18 Dec 2020
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Dongkun Zhang
Lu Lu
Ling Guo
George Karniadakis
UQCV
100
405
0
21 Sep 2018
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations
M. Raissi
George Karniadakis
AI4CE
PINN
65
1,134
0
02 Aug 2017