Towards Fast Simulation of Environmental Fluid Mechanics with
Multi-Scale Graph Neural Networks

Towards Fast Simulation of Environmental Fluid Mechanics with Multi-Scale Graph Neural Networks

5 May 2022

Stathi Fotiadis

Anil A. Bharath

Papers citing "Towards Fast Simulation of Environmental Fluid Mechanics with Multi-Scale Graph Neural Networks"

8 / 8 papers shown

Title
A new graph-based surrogate model for rapid prediction of crashworthiness performance of vehicle panel components Haoran Li Yingxue Zhao Haosu Zhou Tobias Pfaff Nan Li 46 0 0 16 Mar 2025
Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation Shan Zhao Zhaiyu Chen Zhitong Xiong Yilei Shi Sudipan Saha Xiao Xiang Zhu AI4CE 53 3 0 05 Nov 2024
Multiscale Neural Operators for Solving Time-Independent PDEs Winfried Ripken Lisa Coiffard Felix Pieper Sebastian Dziadzio AI4CE 27 2 0 10 Nov 2023
Multi-GPU Approach for Training of Graph ML Models on large CFD Meshes Sebastian Strönisch Maximilian Sander A. Knüpfer M. Meyer AI4CE 25 8 0 25 Jul 2023
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNN Yadi Cao Menglei Chai Minchen Li Chenfanfu Jiang AI4CE 29 19 0 05 Oct 2022
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 265 2,309 0 18 Oct 2020
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 241 439 0 01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 283 1,401 0 01 Dec 2016