vmattey / bc-PINNLinks
A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations
☆32Updated 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☆52Updated 9 months 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-guided neural network framework for elastic plates☆45Updated 3 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 3 years ago
- ☆74Updated 9 months ago
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆66Updated 3 months ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆42Updated last year
- Soving heat transfer problems using PINN with tf2.0☆19Updated 4 years ago
- ☆19Updated last year
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆79Updated last year
- Physics Informed Neural Networks: a starting step for CFD specialists☆34Updated 3 years ago
- Multi-fidelity reduced-order surrogate modeling☆24Updated 2 months ago
- ☆41Updated 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 7 months ago
- ☆28Updated 7 months ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆32Updated last year
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆16Updated last year
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆73Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆51Updated 3 years ago
- ☆21Updated 4 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆56Updated 4 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆32Updated last year
- Tensoflow 2 implementation of physics informed deep learning.☆27Updated 4 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated last year
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 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…☆41Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated 2 years ago
- ☆37Updated last year
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆97Updated 3 years ago