xiaoyuxie-vico / Awesome-ML-PDELinks
Resources about Machine Learning for solving PDEs.
☆58Updated 2 years ago
Alternatives and similar repositories for Awesome-ML-PDE
Users that are interested in Awesome-ML-PDE are comparing it to the libraries listed below
Sorting:
- Encoding physics to learn reaction-diffusion processes☆105Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆38Updated 2 years ago
- Competitive Physics Informed Networks☆31Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- ☆112Updated 8 months ago
- ☆54Updated 3 years ago
- Turbulent flow network source code☆70Updated 7 months ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- PDE Preserved Neural Network☆57Updated 5 months 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
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- ☆50Updated 2 years ago
- ☆60Updated last month
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆62Updated 3 months ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆31Updated 11 months ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆117Updated 2 years ago
- Applications of PINOs☆136Updated 3 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆214Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- ☆60Updated 6 months ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆196Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- ☆28Updated last year
- ☆99Updated 4 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month