mario-linov / graphs4cfdLinks
Graph Neural Networks (GNN) based solvers for Computational Fluid Dynamics (CFD)
☆43Updated last year
Alternatives and similar repositories for graphs4cfd
Users that are interested in graphs4cfd are comparing it to the libraries listed below
Sorting:
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 years ago
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆50Updated 2 years ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆57Updated 9 months ago
- Modified Meshgraphnets with more features☆54Updated 8 months ago
- MIONet: Learning multiple-input operators via tensor product☆38Updated 2 years ago
- Graph Convolutional Networks for Unstructured Flow Fields☆11Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 3 weeks ago
- A GNN-based PDE solver without pre-computed data☆36Updated 3 months ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆31Updated 3 years ago
- ☆27Updated last year
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆62Updated 3 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- PDE Preserved Neural Network☆56Updated 4 months ago
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 7 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated last year
- PINNs for 2D Incompressible Navier-Stokes Equation☆53Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- ☆112Updated 8 months ago
- Laminar flow prediction using graph neural networks☆31Updated 8 months ago
- ☆33Updated 2 months ago
- Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey☆224Updated 4 months ago
- ☆54Updated 2 years ago
- ☆29Updated 8 months ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Encoding physics to learn reaction-diffusion processes☆105Updated 2 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆21Updated 4 months ago
- Multi-fidelity reduced-order surrogate modeling☆25Updated 3 months ago