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Physics-aware deep neural networks for surrogate modeling of turbulent
  natural convection

Physics-aware deep neural networks for surrogate modeling of turbulent natural convection

5 March 2021
Didier Lucor
A. Agrawal
A. Sergent
    PINN
    AI4CE
ArXivPDFHTML

Papers citing "Physics-aware deep neural networks for surrogate modeling of turbulent natural convection"

5 / 5 papers shown
Title
Enhancing accuracy of deep learning algorithms by training with
  low-discrepancy sequences
Enhancing accuracy of deep learning algorithms by training with low-discrepancy sequences
Siddhartha Mishra
T. Konstantin Rusch
68
50
0
26 May 2020
Reservoir computing model of two-dimensional turbulent convection
Reservoir computing model of two-dimensional turbulent convection
S. Pandey
J. Schumacher
51
42
0
28 Jan 2020
Understanding and mitigating gradient pathologies in physics-informed
  neural networks
Understanding and mitigating gradient pathologies in physics-informed neural networks
Sizhuang He
Yujun Teng
P. Perdikaris
AI4CE
PINN
89
294
0
13 Jan 2020
Machine Learning for Fluid Mechanics
Machine Learning for Fluid Mechanics
Steven Brunton
B. R. Noack
Petros Koumoutsakos
AI4CE
PINN
81
2,115
0
27 May 2019
Practical recommendations for gradient-based training of deep
  architectures
Practical recommendations for gradient-based training of deep architectures
Yoshua Bengio
3DH
ODL
185
2,195
0
24 Jun 2012
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