ehsankharazmi / hp-VPINNsLinks
hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations
☆80Updated 3 years ago
Alternatives and similar repositories for hp-VPINNs
Users that are interested in hp-VPINNs are comparing it to the libraries listed below
Sorting:
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆86Updated 4 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆71Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆88Updated last year
- ☆97Updated 3 years ago
- physics-informed neural network for elastodynamics problem☆143Updated 3 years ago
- ☆145Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- POD-PINN code and manuscript☆52Updated 8 months ago
- MIONet: Learning multiple-input operators via tensor product☆34Updated 2 years ago
- ☆111Updated 5 months ago
- DeepONet extrapolation☆27Updated 2 years ago
- Physics-guided neural network framework for elastic plates☆42Updated 3 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 4 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆55Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- ☆54Updated 2 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆93Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- ☆102Updated last year
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆56Updated 4 years ago
- Multifidelity DeepONet☆34Updated 2 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆82Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 3 years ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆40Updated last week
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆149Updated 5 years ago
- PINN program for computational mechanics☆116Updated last year
- Deep Learning of Vortex Induced Vibrations☆97Updated 5 years ago
- hPINN: Physics-informed neural networks with hard constraints☆137Updated 3 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆180Updated 2 years ago