kimy-de / pinnsLinks
Physics-informed neural networks (PINNs)
☆14Updated 3 years ago
Alternatives and similar repositories for pinns
Users that are interested in pinns are comparing it to the libraries listed below
Sorting:
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆58Updated 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…☆43Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆94Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆38Updated 2 years ago
- ☆11Updated last year
- ☆30Updated 3 years ago
- POD-PINN code and manuscript☆57Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆73Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Updated 3 years ago
- Original implementation of fast PINN optimization with RBA weights☆68Updated 4 months ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆32Updated 2 years ago
- Competitive Physics Informed Networks☆32Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 2 months ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- PDE Preserved Neural Network☆59Updated 8 months ago
- ☆54Updated 3 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆107Updated 3 years ago
- Implementation of PINNs in TensorFlow 2☆81Updated last month
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆23Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆43Updated 3 years ago
- ☆117Updated 11 months ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆28Updated 11 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆33Updated 2 years ago
- Laminar flow prediction using graph neural networks☆31Updated last year
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated 4 months ago