ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2110.14121
  4. Cited By
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

27 October 2021
S. Dong
Jielin Yang
ArXivPDFHTML

Papers citing "On Computing the Hyperparameter of Extreme Learning Machines: Algorithm and Application to Computational PDEs, and Comparison with Classical and High-Order Finite Elements"

5 / 5 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 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
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
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
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