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Deep neural network surrogates for non-smooth quantities of interest in
  shape uncertainty quantification

Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification

18 January 2021
L. Scarabosio
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Papers citing "Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification"

3 / 3 papers shown
Title
Physics-informed neural networks for operator equations with stochastic
  data
Physics-informed neural networks for operator equations with stochastic data
Paul Escapil-Inchauspé
G. A. Ruz
26
2
0
15 Nov 2022
An Energy Approach to the Solution of Partial Differential Equations in
  Computational Mechanics via Machine Learning: Concepts, Implementation and
  Applications
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications
E. Samaniego
C. Anitescu
S. Goswami
Vien Minh Nguyen-Thanh
Hongwei Guo
Khader M. Hamdia
Timon Rabczuk
X. Zhuang
PINN
AI4CE
150
1,339
0
27 Aug 2019
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
136
602
0
14 Feb 2016
1