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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
ArXivPDFHTML

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

12 / 12 papers shown
Title
Physics Informed Neural Networks for Simulating Radiative Transfer
Physics Informed Neural Networks for Simulating Radiative Transfer
Siddhartha Mishra
Roberto Molinaro
PINN
65
109
0
25 Sep 2020
Numerical Solution of the Parametric Diffusion Equation by Deep Neural
  Networks
Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks
Moritz Geist
P. Petersen
Mones Raslan
R. Schneider
Gitta Kutyniok
72
83
0
25 Apr 2020
A comprehensive deep learning-based approach to reduced order modeling
  of nonlinear time-dependent parametrized PDEs
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs
S. Fresca
Luca Dede'
Andrea Manzoni
AI4CE
56
262
0
12 Jan 2020
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
182
1,377
0
27 Aug 2019
DeepXDE: A deep learning library for solving differential equations
DeepXDE: A deep learning library for solving differential equations
Lu Lu
Xuhui Meng
Zhiping Mao
George Karniadakis
PINN
AI4CE
95
1,525
0
10 Jul 2019
Nonlinear Approximation and (Deep) ReLU Networks
Nonlinear Approximation and (Deep) ReLU Networks
Ingrid Daubechies
Ronald A. DeVore
S. Foucart
Boris Hanin
G. Petrova
100
141
0
05 May 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
Gitta Kutyniok
P. Petersen
Mones Raslan
R. Schneider
60
198
0
31 Mar 2019
Data-driven discovery of PDEs in complex datasets
Data-driven discovery of PDEs in complex datasets
Jens Berg
K. Nystrom
AI4CE
PINN
46
141
0
31 Aug 2018
Optimal approximation of continuous functions by very deep ReLU networks
Optimal approximation of continuous functions by very deep ReLU networks
Dmitry Yarotsky
176
293
0
10 Feb 2018
Deep UQ: Learning deep neural network surrogate models for high
  dimensional uncertainty quantification
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification
Rohit Tripathy
Ilias Bilionis
AI4CE
60
408
0
02 Feb 2018
Physics Informed Deep Learning (Part I): Data-driven Solutions of
  Nonlinear Partial Differential Equations
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
M. Raissi
P. Perdikaris
George Karniadakis
PINN
AI4CE
75
924
0
28 Nov 2017
The Deep Ritz method: A deep learning-based numerical algorithm for
  solving variational problems
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems
E. Weinan
Ting Yu
117
1,384
0
30 Sep 2017
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