bfly123 / PINN_WELinks
Discontinuity Computing Using Physics-Informed Neural Network
☆24Updated last year
Alternatives and similar repositories for PINN_WE
Users that are interested in PINN_WE are comparing it to the libraries listed below
Sorting:
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- POD-PINN code and manuscript☆51Updated 6 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆34Updated 2 years ago
- Multifidelity DeepONet☆33Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆47Updated last year
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆18Updated 2 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆32Updated last year
- Soving heat transfer problems using PINN with tf2.0☆19Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆70Updated 2 years ago
- ☆29Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆28Updated last year
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆53Updated 4 months ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆27Updated 2 years ago
- ☆26Updated 10 months ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆14Updated last year
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆52Updated 3 years ago
- Physics-informed radial basis network☆30Updated last year
- ☆10Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆35Updated last month
- DeepONet extrapolation☆27Updated 2 years ago
- ☆25Updated 4 months ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 4 months ago
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆39Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆30Updated last year
- Deep finite volume method☆21Updated 11 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆85Updated 4 years ago