punkduckable / PDE-READLinks
☆16Updated 2 years ago
Alternatives and similar repositories for PDE-READ
Users that are interested in PDE-READ are comparing it to the libraries listed below
Sorting:
- ☆14Updated 3 weeks ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆25Updated 2 years ago
- The MegaFlow2D dataset package☆24Updated 2 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 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
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆20Updated 4 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 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…☆58Updated last year
- MIONet: Learning multiple-input operators via tensor product☆44Updated 3 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆18Updated last year
- ☆54Updated 3 years ago
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Updated 2 years ago
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆39Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆37Updated 2 months ago
- Competitive Physics Informed Networks☆32Updated last year
- KTH-FlowAI / beta-Variational-autoencoders-and-transformers-for-reduced-order-modelling-of-fluid-flows☆42Updated 9 months ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆29Updated 4 years ago
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆26Updated last year
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆20Updated last year
- ☆16Updated 2 years ago
- 采用PINN/ResPINN对两种偏微分方程(Burgers&Allen-Cahn)的训练与求解☆16Updated 5 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆28Updated last year
- POD-PINN code and manuscript☆57Updated last year
- ☆29Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆77Updated 2 years ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆36Updated last year
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 11 months ago