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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

14 January 2022
S. Cuomo
Vincenzo Schiano Di Cola
F. Giampaolo
G. Rozza
Maizar Raissi
F. Piccialli
    PINN
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Papers citing "Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next"

5 / 105 papers shown
Title
Machine Learning of Linear Differential Equations using Gaussian
  Processes
Machine Learning of Linear Differential Equations using Gaussian Processes
M. Raissi
George Karniadakis
58
544
0
10 Jan 2017
Error bounds for approximations with deep ReLU networks
Error bounds for approximations with deep ReLU networks
Dmitry Yarotsky
137
1,226
0
03 Oct 2016
Inferring solutions of differential equations using noisy multi-fidelity
  data
Inferring solutions of differential equations using noisy multi-fidelity data
M. Raissi
P. Perdikaris
George Karniadakis
AI4CE
41
288
0
16 Jul 2016
Understanding Deep Convolutional Networks
Understanding Deep Convolutional Networks
S. Mallat
FAtt
AI4CE
105
639
0
19 Jan 2016
Bayesian Numerical Homogenization
Bayesian Numerical Homogenization
H. Owhadi
62
234
0
25 Jun 2014
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