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Learning governing physics from output only measurements

Learning governing physics from output only measurements

Tapas Tripura
S. Chakraborty
ArXiv (abs)PDFHTML

Papers citing "Learning governing physics from output only measurements"

6 / 6 papers shown
Title
A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems
A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems
Tapas Tripura
M. Imran
B. Hazra
S. Chakraborty
26
7
0
24 Aug 2021
Bayesian equation selection on sparse data for discovery of stochastic dynamical systems
Bayesian equation selection on sparse data for discovery of stochastic dynamical systems
Kushagra Gupta
Dootika Vats
Snigdhansu Chatterjee
46
3
0
12 Jan 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
500
2,414
0
18 Oct 2020
Transfer learning based multi-fidelity physics informed deep neural network
Transfer learning based multi-fidelity physics informed deep neural network
S. Chakraborty
PINNOODAI4CE
72
165
0
19 May 2020
Simulation free reliability analysis: A physics-informed deep learning based approach
Simulation free reliability analysis: A physics-informed deep learning based approach
S. Chakraborty
AI4CE
33
16
0
04 May 2020
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture
S. Goswami
C. Anitescu
S. Chakraborty
Timon Rabczuk
PINN
75
610
0
04 Jul 2019