vmattey / bc-PINNLinks
A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations
☆34Updated 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☆54Updated 11 months ago
- Physics-guided neural network framework for elastic plates☆46Updated 3 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
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated last year
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆58Updated 4 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆84Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 9 months ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆92Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆69Updated 3 weeks ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆44Updated last year
- 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: a starting step for CFD specialists☆37Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆84Updated 2 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 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…☆43Updated 2 years ago
- ☆19Updated last year
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆77Updated 4 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- ☆30Updated 9 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- Yet another PINN implementation☆20Updated last year
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆68Updated 5 months ago
- ☆41Updated 3 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated last year
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆33Updated 3 years ago
- Competitive Physics Informed Networks☆31Updated last year