guodongsanjianke / Neural-Network-for-solving-PDELinks
Different methods of solving partial differential equations with neural networks
☆17Updated 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
Sorting:
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 5 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆177Updated 4 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆74Updated 3 years ago
- A Physics-Informed Neural Network for solving Burgers' equation.☆33Updated last year
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆118Updated 6 years ago
- POD-PINN code and manuscript☆52Updated 9 months ago
- ETH Zürich AI in the Sciences and Engineering Master's course 2024☆39Updated last year
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆23Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- ☆21Updated 4 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…☆41Updated 2 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- ☆10Updated 4 years ago
- ☆54Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆24Updated last month
- ☆63Updated 6 years ago
- Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics☆63Updated 3 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated 11 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
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆18Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆80Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- Competitive Physics Informed Networks☆31Updated 10 months ago
- ☆42Updated 5 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago