chiuph / CAN-PINNLinks
Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)
☆33Updated 2 years ago
Alternatives and similar repositories for CAN-PINN
Users that are interested in CAN-PINN are comparing it to the libraries listed below
Sorting:
- ☆54Updated 3 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆39Updated 2 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆38Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- POD-PINN code and manuscript☆57Updated last year
- ☆30Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 4 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆28Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 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 last year
- MIONet: Learning multiple-input operators via tensor product☆43Updated 3 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆32Updated 2 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- ☆117Updated 11 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Updated 4 years ago
- Graph Convolutional Networks for Unstructured Flow Fields☆13Updated 3 years ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆69Updated 2 months ago
- ☆110Updated 4 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆58Updated last year
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆54Updated 2 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 2 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆94Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆45Updated 3 years ago
- Physics-informed radial basis network☆35Updated last year
- PDE Preserved Neural Network☆59Updated 8 months ago