guodongsanjianke / Neural-Network-for-solving-PDE
Different methods of solving partial differential equations with neural networks
☆15Updated 3 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
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 4 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆23Updated last year
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆29Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 3 months ago
- ☆62Updated 5 years ago
- POD-PINN code and manuscript☆48Updated 4 months ago
- Sparse Physics-based and Interpretable Neural Networks☆47Updated 3 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆17Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆32Updated 8 months ago
- ☆33Updated 3 months ago
- Machine learning of linear differential equations using Gaussian processes☆24Updated 6 years ago
- Yet another PINN implementation☆20Updated 9 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- ☆18Updated 4 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 3 years ago
- Implementing a physics-informed DeepONet from scratch☆36Updated last year
- ☆28Updated last year
- Physics Informed Neural Network (PINN) for Burgers' equation.☆69Updated 7 months ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆17Updated 2 years ago
- Python tools for non-intrusive reduced order modeling☆18Updated 8 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆19Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆46Updated 2 years ago
- ☆41Updated 4 years ago
- PDE Preserved Neural Network☆46Updated 8 months ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆23Updated 2 months ago
- ☆10Updated 4 years ago