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Deep least-squares methods: an unsupervised learning-based numerical
  method for solving elliptic PDEs

Deep least-squares methods: an unsupervised learning-based numerical method for solving elliptic PDEs

5 November 2019
Z. Cai
Jingshuang Chen
Min Liu
Xinyu Liu
ArXivPDFHTML

Papers citing "Deep least-squares methods: an unsupervised learning-based numerical method for solving elliptic PDEs"

10 / 10 papers shown
Title
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method
Conor Rowan
K. Maute
Alireza Doostan
AI4CE
48
0
0
08 May 2025
Efficient Shallow Ritz Method For 1D Diffusion-Reaction Problems
Efficient Shallow Ritz Method For 1D Diffusion-Reaction Problems
Zhiqiang Cai
Anastassia Doktorova
Robert D. Falgout
César Herrera
19
0
0
01 Jul 2024
Astral: training physics-informed neural networks with error majorants
Astral: training physics-informed neural networks with error majorants
V. Fanaskov
Tianchi Yu
Alexander Rudikov
Ivan Oseledets
41
1
0
04 Jun 2024
Error Analysis of Physics-Informed Neural Networks for Approximating
  Dynamic PDEs of Second Order in Time
Error Analysis of Physics-Informed Neural Networks for Approximating Dynamic PDEs of Second Order in Time
Y. Qian
Yongchao Zhang
Yuanfei Huang
S. Dong
PINN
21
1
0
22 Mar 2023
$r-$Adaptive Deep Learning Method for Solving Partial Differential
  Equations
r−r-r−Adaptive Deep Learning Method for Solving Partial Differential Equations
Ángel J. Omella
David Pardo
AI4CE
31
4
0
19 Oct 2022
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks
Zhiwei Bai
Tao Luo
Z. Xu
Yaoyu Zhang
31
4
0
26 May 2022
DeepParticle: learning invariant measure by a deep neural network
  minimizing Wasserstein distance on data generated from an interacting
  particle method
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method
Zhongjian Wang
Jack Xin
Zhiwen Zhang
39
15
0
02 Nov 2021
Self-adaptive deep neural network: Numerical approximation to functions
  and PDEs
Self-adaptive deep neural network: Numerical approximation to functions and PDEs
Zhiqiang Cai
Jingshuang Chen
Min Liu
ODL
15
14
0
07 Sep 2021
SPINN: Sparse, Physics-based, and partially Interpretable Neural
  Networks for PDEs
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs
A. A. Ramabathiran
P. Ramachandran
PINN
AI4CE
27
76
0
25 Feb 2021
Reproducing Activation Function for Deep Learning
Reproducing Activation Function for Deep Learning
Senwei Liang
Liyao Lyu
Chunmei Wang
Haizhao Yang
36
21
0
13 Jan 2021
1