guodongsanjianke / Neural-Network-for-solving-PDELinks
Different methods of solving partial differential equations with neural networks
☆18Updated 4 years ago
Alternatives and similar repositories for Neural-Network-for-solving-PDE
Users that are interested in Neural-Network-for-solving-PDE are comparing it to the libraries listed below
Sorting:
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 5 years ago
- ☆21Updated 5 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆78Updated 3 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆43Updated 2 years ago
- ☆55Updated 3 years ago
- ☆50Updated 2 years ago
- Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics☆65Updated 3 years ago
- ☆12Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- POD-PINN code and manuscript☆54Updated 11 months ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆18Updated 3 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆38Updated 11 months ago
- ☆10Updated 4 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆201Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆84Updated 2 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆92Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆15Updated 4 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆26Updated 9 months ago
- ☆63Updated 6 years ago
- ☆42Updated 5 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆34Updated 3 years ago