rsmath / dt-pinn
Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations
☆25Updated last year
Alternatives and similar repositories for dt-pinn:
Users that are interested in dt-pinn are comparing it to the libraries listed below
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆25Updated last year
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 10 months ago
- ☆26Updated 2 years ago
- POD-PINN code and manuscript☆48Updated 4 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- Multifidelity DeepONet☆29Updated last year
- Physics-informed radial basis network☆30Updated 9 months ago
- DeepONet extrapolation☆26Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆21Updated last year
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆39Updated 2 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆10Updated 3 years ago
- MIONet: Learning multiple-input operators via tensor product☆32Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆49Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆12Updated 10 months ago
- Sparse Physics-based and Interpretable Neural Networks☆47Updated 3 years ago
- Physics-informed neural networks for identifying material properties in solid mechanics☆16Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆22Updated last month
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆35Updated 6 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆19Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆28Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆82Updated 4 years ago
- ☆28Updated 2 years ago
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 5 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆32Updated 8 months ago
- ☆38Updated last year
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆21Updated last year
- ☆35Updated 2 years ago
- Original implementation of fast PINN optimization with RBA weights☆48Updated 4 months ago
- ☆52Updated 2 years ago