Graph Neural Network-based Surrogate Models for Finite Element Analysis

17 November 2022

Papers citing "Graph Neural Network-based Surrogate Models for Finite Element Analysis"

5 / 5 papers shown

Title
Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks A. Celaya Yimo Wang David T. Fuentes Beatrice Riviere 38 0 0 12 Feb 2025
Predicting Wall Thickness Changes in Cold Forging Processes: An Integrated FEM and Neural Network approach Sasa Ilic Abdulkerim Karaman Johannes Pöppelbaum Jan Niclas Reimann Michael Marré Andreas Schwung AI4CE 62 0 0 20 Nov 2024
A Hybrid GNN approach for predicting node data for 3D meshes Shwetha Salimath Francesca Bugiotti Frédéric Magoulès AI4CE 17 0 0 23 Oct 2023
Physics-Informed Graph Convolutional Networks: Towards a generalized framework for complex geometries M. Chenaud José Alves Frédéric Magoulès AI4CE PINN 21 1 0 20 Oct 2023
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 219 14,047 0 02 Dec 2016