TamaraGrossmann / FEM-vs-PINNsLinks
☆104Updated last year
Alternatives and similar repositories for FEM-vs-PINNs
Users that are interested in FEM-vs-PINNs are comparing it to the libraries listed below
Sorting:
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆187Updated 2 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆209Updated 2 years ago
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…☆116Updated last month
- ☆69Updated last year
- physics-informed neural network for elastodynamics problem☆146Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆73Updated 2 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆51Updated 3 years ago
- ☆98Updated 3 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆150Updated 5 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆82Updated 3 weeks ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- ☆150Updated 3 years ago
- ☆112Updated 7 months ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆75Updated 3 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆69Updated 2 years ago
- Deep Learning for Reduced Order Modelling☆100Updated 3 years ago
- Physics Informed Neural Network (PINN) for the wave equation.☆186Updated 5 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆113Updated 2 years ago
- A place to share problems solved with SciANN☆287Updated last year
- DeepXDE and PINN☆128Updated 3 years ago
- PINN program for computational mechanics☆119Updated last year
- Basic implementation of physics-informed neural network with pytorch.☆77Updated 2 years ago
- ☆52Updated 9 months ago
- Generative Pre-Trained Physics-Informed Neural Networks Implementation☆104Updated 3 weeks ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated 2 years ago
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆52Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆248Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago