junbinhuang / DeepRitzLinks
Implementation of the Deep Ritz method and the Deep Galerkin method
☆60Updated 5 years ago
Alternatives and similar repositories for DeepRitz
Users that are interested in DeepRitz are comparing it to the libraries listed below
Sorting:
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆84Updated 2 months ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆251Updated 4 years ago
- ☆99Updated 4 years ago
- ☆152Updated 3 years ago
- hPINN: Physics-informed neural networks with hard constraints☆147Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆92Updated 2 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆199Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆225Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 5 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆78Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆216Updated 2 years ago
- ☆114Updated 8 months ago
- ☆63Updated 6 years ago
- ☆178Updated last year
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆38Updated 11 months ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆143Updated 3 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆152Updated 5 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆161Updated last year
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 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…☆43Updated 2 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆90Updated 3 years ago
- ☆131Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆154Updated 2 years ago
- PINN in solving Navier–Stokes equation☆113Updated 5 years ago