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A Modified Batch Intrinsic Plasticity Method for Pre-training the Random
  Coefficients of Extreme Learning Machines

A Modified Batch Intrinsic Plasticity Method for Pre-training the Random Coefficients of Extreme Learning Machines

14 March 2021
S. Dong
Zongwei Li
ArXivPDFHTML

Papers citing "A Modified Batch Intrinsic Plasticity Method for Pre-training the Random Coefficients of Extreme Learning Machines"

11 / 11 papers shown
Title
Weak baselines and reporting biases lead to overoptimism in machine
  learning for fluid-related partial differential equations
Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations
N. McGreivy
Ammar Hakim
AI4CE
34
43
0
09 Jul 2024
Error Analysis and Numerical Algorithm for PDE Approximation with
  Hidden-Layer Concatenated Physics Informed Neural Networks
Error Analysis and Numerical Algorithm for PDE Approximation with Hidden-Layer Concatenated Physics Informed Neural Networks
Yianxia Qian
Yongchao Zhang
Suchuan Dong
PINN
37
0
0
10 Jun 2024
An Extreme Learning Machine-Based Method for Computational PDEs in
  Higher Dimensions
An Extreme Learning Machine-Based Method for Computational PDEs in Higher Dimensions
Yiran Wang
Suchuan Dong
31
35
0
13 Sep 2023
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
A Method for Computing Inverse Parametric PDE Problems with
  Random-Weight Neural Networks
A Method for Computing Inverse Parametric PDE Problems with Random-Weight Neural Networks
S. Dong
Yiran Wang
29
20
0
09 Oct 2022
Numerical Computation of Partial Differential Equations by Hidden-Layer
  Concatenated Extreme Learning Machine
Numerical Computation of Partial Differential Equations by Hidden-Layer Concatenated Extreme Learning Machine
Naxian Ni
S. Dong
29
20
0
24 Apr 2022
Parsimonious Physics-Informed Random Projection Neural Networks for
  Initial-Value Problems of ODEs and index-1 DAEs
Parsimonious Physics-Informed Random Projection Neural Networks for Initial-Value Problems of ODEs and index-1 DAEs
Gianluca Fabiani
Evangelos Galaris
L. Russo
Constantinos Siettos
6
29
0
10 Mar 2022
Numerical Approximation of Partial Differential Equations by a Variable
  Projection Method with Artificial Neural Networks
Numerical Approximation of Partial Differential Equations by a Variable Projection Method with Artificial Neural Networks
S. Dong
Jielin Yang
40
17
0
24 Jan 2022
On Computing the Hyperparameter of Extreme Learning Machines: Algorithm
  and Application to Computational PDEs, and Comparison with Classical and
  High-Order Finite Elements
On Computing the Hyperparameter of Extreme Learning Machines: Algorithm and Application to Computational PDEs, and Comparison with Classical and High-Order Finite Elements
S. Dong
Jielin Yang
76
52
0
27 Oct 2021
Numerical Solution of Stiff ODEs with Physics-Informed RPNNs
Numerical Solution of Stiff ODEs with Physics-Informed RPNNs
Evangelos Galaris
Gianluca Fabiani
Francesco Calabrò
D. Serafino
Constantinos Siettos
14
2
0
03 Aug 2021
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
159
1,342
0
27 Aug 2019
1