weipengOO98 / rang_pinnLinks
Code for reproducing the paper: RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks
☆16Updated 3 years ago
Alternatives and similar repositories for rang_pinn
Users that are interested in rang_pinn are comparing it to the libraries listed below
Sorting:
- 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…☆43Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆85Updated 3 months ago
- Pytorch implementation of Bayesian physics-informed neural networks☆67Updated 4 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- ☆158Updated 3 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆103Updated 3 years ago
- physics-informed neural network for elastodynamics problem☆152Updated 3 years ago
- PINN for solving wave equation☆21Updated 2 years ago
- U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow☆158Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Physics Informed Fourier Neural Operator☆23Updated last year
- POD-PINN code and manuscript☆56Updated last year
- 2nd Order Wave Equation PINN Solution/ TensorFlow & PyTorch☆28Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- ☆105Updated 4 years ago
- ☆38Updated 2 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆73Updated 2 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆93Updated 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…☆27Updated 10 months ago
- ☆54Updated 3 years ago
- MIONet: Learning multiple-input operators via tensor product☆39Updated 3 years ago
- Original implementation of fast PINN optimization with RBA weights☆68Updated 2 months ago
- Deep learning library for solving differential equations on top of PyTorch.☆62Updated 5 years ago
- Physics-Informed Neural Networks designed to solve the Two-Dimensional Wave Equation in both TensorFlow and PyTorch. Code is designed to …☆17Updated 3 years ago
- ☆52Updated 11 months ago