Image de couverture de livre

X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Nabian, Mohammad Amin, Liu, Chang, Ranade, Rishikesh, Choudhry, Sanjay
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Computational Physics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations
par: Ranade, Rishikesh, et autres
Publié: (2025)

GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer
par: Adams, Corey, et autres
Publié: (2025)

Accelerating Transient CFD through Machine Learning-Based Flow Initialization
par: Sharpe, Peter, et autres
Publié: (2025)

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics
par: Nabian, Mohammad Amin, et autres
Publié: (2025)

MeshGraphNet-Transformer: Scalable Mesh-based Learned Simulation for Solid Mechanics
par: Iparraguirre, Mikel M., et autres
Publié: (2026)

Automotive Crash Dynamics Modeling Accelerated with Machine Learning
par: Nabian, Mohammad Amin, et autres
Publié: (2025)

High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention
par: Akhare, Deepak, et autres
Publié: (2026)

A Benchmarking Framework for AI models in Automotive Aerodynamics
par: Tangsali, Kaustubh, et autres
Publié: (2025)

Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes
par: Würth, Tobias, et autres
Publié: (2024)

Generalization capabilities of MeshGraphNets to unseen geometries for fluid dynamics
par: Schmöcker, Robin, et autres
Publié: (2024)

MoWE : A Mixture of Weather Experts
par: Chakraborty, Dibyajyoti, et autres
Publié: (2025)

Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling
par: Barwey, Shivam, et autres
Publié: (2024)

One-shot learning for solution operators of partial differential equations
par: Jiao, Anran, et autres
Publié: (2021)

MeshODENet: A Graph-Informed Neural Ordinary Differential Equation Neural Network for Simulating Mesh-Based Physical Systems
par: Liu, Kangzheng, et autres
Publié: (2025)

M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations
par: Lei, Bo, et autres
Publié: (2025)

GemNet: Universal Directional Graph Neural Networks for Molecules
par: Gasteiger, Johannes, et autres
Publié: (2021)

Disentangling History and Propagation Dependencies in Cross-Subject Knee Contact Stress Prediction Using a Shared MeshGraphNet Backbone
par: Pan, Zhengye, et autres
Publié: (2026)

Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem
par: Lee, Youngkyu, et autres
Publié: (2024)

Data-driven modeling of shock physics by physics-informed MeshGraphNets
par: Zhang, S., et autres
Publié: (2026)

Dynami-CAL GraphNet: A Physics-Informed Graph Neural Network Conserving Linear and Angular Momentum for Dynamical Systems
par: Sharma, Vinay, et autres
Publié: (2025)

Sampling-based Distributed Training with Message Passing Neural Network
par: Kakka, Priyesh, et autres
Publié: (2024)

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
par: Wang, Huaxin, et autres
Publié: (2026)

Diffusion-Based Hierarchical Graph Neural Networks for Simulating Nonlinear Solid Mechanics
par: Würth, Tobias, et autres
Publié: (2025)

Graph Network-based Structural Simulator: Graph Neural Networks for Structural Dynamics
par: Lucchetti, Alessandro, et autres
Publié: (2025)

Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
par: Barwey, Shivam, et autres
Publié: (2024)

Graph Convolutional Networks for Simulating Multi-phase Flow and Transport in Porous Media
par: Jiang, Jiamin, et autres
Publié: (2023)

Equi-Euler GraphNet: An Equivariant, Temporal-Dynamics Informed Graph Neural Network for Dual Force and Trajectory Prediction in Multi-Body Systems
par: Sharma, Vinay, et autres
Publié: (2025)

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
par: Garnier, Paul, et autres
Publié: (2025)

MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations
par: Deshpande, Saurabh, et autres
Publié: (2022)

Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles
par: Vinchurkar, Tirtha, et autres
Publié: (2025)

Large Scale Training of Graph Neural Networks for Optimal Markov-Chain Partitioning Using the Kemeny Constant
par: Martino, Sam Alexander, et autres
Publié: (2023)

Transfer learning in Scalable Graph Neural Network for Improved Physical Simulation
par: Shen, Siqi, et autres
Publié: (2025)

Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
par: Shi, Guangsi, et autres
Publié: (2023)

Automated discovery of finite volume schemes using Graph Neural Networks
par: Garnier, Paul, et autres
Publié: (2025)

CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation
par: Elrefaie, Mohamed, et autres
Publié: (2026)

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations
par: Pelaez, Raul P., et autres
Publié: (2024)

Robust Topology Optimization Using Multi-Fidelity Variational Autoencoders
par: Gladstone, Rini Jasmine, et autres
Publié: (2021)

EvoMesh: Adaptive Physical Simulation with Hierarchical Graph Evolutions
par: Deng, Huayu, et autres
Publié: (2024)

Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction
par: Kaniselvan, Manasa, et autres
Publié: (2025)

Learning to Simulate Aerosol Dynamics with Graph Neural Networks
par: Ferracina, Fabiana, et autres
Publié: (2024)