vmattey / bc-PINNLinks
A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations
☆31Updated 3 years ago
Alternatives and similar repositories for bc-PINN
Users that are interested in bc-PINN are comparing it to the libraries listed below
Sorting:
- POD-PINN code and manuscript☆51Updated 6 months ago
- Physics-guided neural network framework for elastic plates☆39Updated 3 years ago
- Contains implementation of PINN using Tensorflow 2.4.0☆14Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆26Updated 2 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆32Updated 2 years ago
- Physics Informed Neural Networks: a starting step for CFD specialists☆31Updated 3 years ago
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 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…☆40Updated 2 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated last year
- Physics Informed Neural Networks (based on Raissi et al) extended to three dimensions on the heat diffusion equations☆18Updated 2 years ago
- Soving heat transfer problems using PINN with tf2.0☆19Updated 3 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 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…☆25Updated 4 months ago
- Multifidelity DeepONet☆33Updated last year
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆55Updated 4 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆78Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆60Updated 3 weeks ago
- Pytorch implementation of Bayesian physics-informed neural networks☆59Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Direct and Inverse Heat Conduction Problems☆13Updated 2 years ago
- ☆19Updated last year
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆38Updated this week
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆38Updated 9 months ago
- gPINN: Gradient-enhanced physics-informed neural networks☆91Updated 3 years ago
- ☆38Updated 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…☆14Updated last year
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆49Updated 2 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆70Updated 2 years ago
- A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations☆18Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆72Updated last year