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Data-driven learning of robust nonlocal physics from high-fidelity
  synthetic data

Data-driven learning of robust nonlocal physics from high-fidelity synthetic data

17 May 2020
Huaiqian You
Yue Yu
Nathaniel Trask
Mamikon A. Gulian
M. DÉlia
ArXivPDFHTML

Papers citing "Data-driven learning of robust nonlocal physics from high-fidelity synthetic data"

5 / 5 papers shown
Title
nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized
  nonlocal universal Laplacian operator. Algorithms and Applications
nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications
G. Pang
M. DÉlia
M. Parks
George Karniadakis
PINN
48
154
0
08 Apr 2020
Robust Training and Initialization of Deep Neural Networks: An Adaptive
  Basis Viewpoint
Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint
E. Cyr
Mamikon A. Gulian
Ravi G. Patel
M. Perego
N. Trask
80
72
0
10 Dec 2019
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
376
42,299
0
03 Dec 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks
DAG-GNN: DAG Structure Learning with Graph Neural Networks
Yue Yu
Jie Chen
Tian Gao
Mo Yu
BDL
CML
GNN
67
485
0
22 Apr 2019
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.5K
149,842
0
22 Dec 2014
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