paulpuren / PhyCRNetLinks
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
☆30Updated 3 years ago
Alternatives and similar repositories for PhyCRNet
Users that are interested in PhyCRNet are comparing it to the libraries listed below
Sorting:
- PINNs for 2D Incompressible Navier-Stokes Equation☆53Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 8 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated last year
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆77Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆58Updated 4 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆12Updated 3 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆37Updated 2 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆17Updated last year
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆33Updated 3 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆31Updated 3 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆29Updated 2 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆22Updated 2 years ago
- ☆41Updated 3 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 2 years ago
- Competitive Physics Informed Networks☆31Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆43Updated 3 weeks ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆156Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆76Updated 4 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Research/development of physics-informed neural networks for dynamic systems☆29Updated 10 months ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 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…☆42Updated 2 years ago
- Yet another PINN implementation☆20Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago