Rui1521 / Turbulent-Flow-NetsLinks
Towards Physics-informed Deep Learning for Turbulent Flow Prediction
☆27Updated 3 years ago
Alternatives and similar repositories for Turbulent-Flow-Nets
Users that are interested in Turbulent-Flow-Nets are comparing it to the libraries listed below
Sorting:
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆50Updated 2 years ago
- ☆59Updated last month
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 years ago
- ☆54Updated 2 years ago
- Physics-encoded recurrent convolutional neural network☆46Updated 3 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…☆56Updated 8 months ago
- PDE Preserved Neural Network☆55Updated 4 months ago
- MIONet: Learning multiple-input operators via tensor product☆37Updated 2 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated this week
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆69Updated 4 months ago
- Turbulent flow network source code☆70Updated 6 months ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆55Updated 2 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆51Updated 3 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆30Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated 2 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- ☆64Updated 2 years ago
- ☆63Updated 6 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- KTH-FlowAI / beta-Variational-autoencoders-and-transformers-for-reduced-order-modelling-of-fluid-flows☆33Updated 4 months ago
- Graph Neural Networks (GNN) based solvers for Computational Fluid Dynamics (CFD)☆42Updated last year
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 6 months ago
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆20Updated 3 months ago
- ☆13Updated 5 years ago
- ☆35Updated 4 years ago