Importance of equivariant and invariant symmetries for fluid flow modeling

3 May 2023

Papers citing "Importance of equivariant and invariant symmetries for fluid flow modeling"

5 / 5 papers shown

Title
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks Shivam Barwey Pinaki Pal Saumil Patel Riccardo Balin Bethany Lusch V. Vishwanath R. Maulik R. Balakrishnan AI4CE 86 0 0 12 Sep 2024
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 42 39 0 16 May 2022
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models Julian Suk P. D. Haan Phillip Lippe Christoph Brune J. Wolterink AI4CE 45 19 0 10 Sep 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 183 1,218 0 08 Jan 2021
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud Weijing Shi Ragunathan R. Rajkumar 3DPC 133 615 0 02 Mar 2020