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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

18 December 2020
Li Wang
Zhenya Yan
ArXivPDFHTML

Papers citing "Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning"

10 / 10 papers shown
Title
Data assimilation and parameter identification for water waves using the
  nonlinear Schrödinger equation and physics-informed neural networks
Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks
Svenja Ehlers
Niklas A. Wagner
Annamaria Scherzl
Marco Klein
Norbert Hoffmann
M. Stender
16
1
0
08 Jan 2024
Deep learning soliton dynamics and complex potentials recognition for 1D
  and 2D PT-symmetric saturable nonlinear Schrödinger equations
Deep learning soliton dynamics and complex potentials recognition for 1D and 2D PT-symmetric saturable nonlinear Schrödinger equations
Jin Song
Ilya Shenbin
86
25
0
29 Sep 2023
Data-driven localized waves and parameter discovery in the massive
  Thirring model via extended physics-informed neural networks with interface
  zones
Data-driven localized waves and parameter discovery in the massive Thirring model via extended physics-informed neural networks with interface zones
Christian Berger
Sadok Ben Toumia
Zijian Zhou
Zhenya Yan
PINN
23
8
0
29 Sep 2023
Data-driven modeling of Landau damping by physics-informed neural
  networks
Data-driven modeling of Landau damping by physics-informed neural networks
Yilan Qin
Jiayu Ma
M. Jiang
C. Dong
H. Fu
Liang Wang
Wen-jie Cheng
Yaqiu Jin
PINN
AI4CE
13
7
0
02 Nov 2022
Enforcing continuous symmetries in physics-informed neural network for
  solving forward and inverse problems of partial differential equations
Enforcing continuous symmetries in physics-informed neural network for solving forward and inverse problems of partial differential equations
Zhi‐Yong Zhang
Hui Zhang
Li-sheng Zhang
Lei‐Lei Guo
PINN
AI4CE
12
27
0
19 Jun 2022
Scientific Machine Learning through Physics-Informed Neural Networks:
  Where we are and What's next
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next
S. Cuomo
Vincenzo Schiano Di Cola
F. Giampaolo
G. Rozza
Maizar Raissi
F. Piccialli
PINN
26
1,177
0
14 Jan 2022
Deep neural networks for solving forward and inverse problems of
  (2+1)-dimensional nonlinear wave equations with rational solitons
Deep neural networks for solving forward and inverse problems of (2+1)-dimensional nonlinear wave equations with rational solitons
Zijian Zhou
Li Wang
Zhenya Yan
8
1
0
28 Dec 2021
Data-driven discoveries of Bäcklund transforms and soliton evolution
  equations via deep neural network learning schemes
Data-driven discoveries of Bäcklund transforms and soliton evolution equations via deep neural network learning schemes
Zijian Zhou
Li Wang
Weifang Weng
Zhenya Yan
8
17
0
18 Nov 2021
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
9
33
0
30 Apr 2021
Data-driven peakon and periodic peakon travelling wave solutions of some
  nonlinear dispersive equations via deep learning
Data-driven peakon and periodic peakon travelling wave solutions of some nonlinear dispersive equations via deep learning
Li Wang
Zhenya Yan
74
47
0
12 Jan 2021
1