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. 2402.10681
  4. Cited By
Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers
  for non-stationary and nonlinear simulations on arbitrary meshes

Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes

16 February 2024
Tobias Würth
Niklas Freymuth
C. Zimmerling
Gerhard Neumann
Luise Kärger
    AI4CE
ArXivPDFHTML

Papers citing "Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes"

2 / 2 papers shown
Title
Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed
  Boundary Conditions
Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions
Masanobu Horie
Naoto Mitsume
PINN
AI4CE
23
23
0
24 May 2022
Physics-informed Convolutional Neural Networks for Temperature Field
  Prediction of Heat Source Layout without Labeled Data
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
Xiaoyu Zhao
Zhiqiang Gong
Yunyang Zhang
Wen Yao
Xiaoqian Chen
OOD
AI4CE
69
91
0
26 Sep 2021
1