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Deep neural network enabled corrective source term approach to hybrid
  analysis and modeling

Deep neural network enabled corrective source term approach to hybrid analysis and modeling

24 May 2021
Sindre Stenen Blakseth
Adil Rasheed
T. Kvamsdal
Omer San
ArXivPDFHTML

Papers citing "Deep neural network enabled corrective source term approach to hybrid analysis and modeling"

14 / 14 papers shown
Title
Hybrid analysis and modeling, eclecticism, and multifidelity computing
  toward digital twin revolution
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
Omer San
Adil Rasheed
T. Kvamsdal
75
51
0
26 Mar 2021
Physics guided machine learning using simplified theories
Physics guided machine learning using simplified theories
Suraj Pawar
Omer San
Burak Aksoylu
Adil Rasheed
T. Kvamsdal
PINN
AI4CE
117
106
0
18 Dec 2020
A Probabilistic Graphical Model Foundation for Enabling Predictive
  Digital Twins at Scale
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale
Michael G. Kapteyn
Jacob V. R. Pretorius
Karen E. Willcox
44
222
0
10 Dec 2020
The role of surrogate models in the development of digital twins of
  dynamic systems
The role of surrogate models in the development of digital twins of dynamic systems
S. Chakraborty
S. Adhikari
R. Ganguli
SyDa
33
104
0
25 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
292
42,038
0
03 Dec 2019
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs
Xuhui Meng
Zhen Li
Dongkun Zhang
George Karniadakis
PINN
AI4CE
39
446
0
23 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Han Xu
Yao Ma
Haochen Liu
Debayan Deb
Hui Liu
Jiliang Tang
Anil K. Jain
AAML
62
673
0
17 Sep 2019
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A
  Survey
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Ajmal Mian
AAML
64
1,862
0
02 Jan 2018
Adversarial Examples: Attacks and Defenses for Deep Learning
Adversarial Examples: Attacks and Defenses for Deep Learning
Xiaoyong Yuan
Pan He
Qile Zhu
Xiaolin Li
SILM
AAML
67
1,614
0
19 Dec 2017
Joint Gaussian Processes for Biophysical Parameter Retrieval
Joint Gaussian Processes for Biophysical Parameter Retrieval
D. Svendsen
Luca Martino
M. Campos-Taberner
F. J. García-Haro
Gustau Camps-Valls
25
49
0
14 Nov 2017
Deep Convolutional Neural Network for Inverse Problems in Imaging
Deep Convolutional Neural Network for Inverse Problems in Imaging
Kyong Hwan Jin
Michael T. McCann
Emmanuel Froustey
M. Unser
45
2,116
0
11 Nov 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
306
14,196
0
23 Feb 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
979
149,474
0
22 Dec 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
192
14,831
1
21 Dec 2013
1