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FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical
  Response Prediction

FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction

31 January 2020
Houpu Yao
Yi Gao
Yongming Liu
    AI4CE
ArXivPDFHTML

Papers citing "FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction"

3 / 3 papers shown
Title
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations
Hamidreza Eivazi
Jendrik-Alexander Tröger
Stefan H. A. Wittek
Stefan Hartmann
Andreas Rausch
AI4CE
41
0
0
27 Mar 2025
Multi-resolution partial differential equations preserved learning
  framework for spatiotemporal dynamics
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics
Xin-Yang Liu
Min Zhu
Lu Lu
Hao Sun
Jian-Xun Wang
PINN
AI4CE
14
45
0
09 May 2022
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for
  Parametric PDEs
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs
Biswajit Khara
Aditya Balu
Ameya Joshi
S. Sarkar
C. Hegde
A. Krishnamurthy
Baskar Ganapathysubramanian
14
19
0
04 Oct 2021
1