junbinhuang / DeepRitz
Implementation of the Deep Ritz method and the Deep Galerkin method
☆52Updated 4 years ago
Alternatives and similar repositories for DeepRitz:
Users that are interested in DeepRitz are comparing it to the libraries listed below
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 4 years ago
- Group project for Deep Learning: Algorithms and Applications in Peking University 2018 Spring. This is a brief survey, discussion and imp…☆44Updated 6 years ago
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆113Updated 5 years ago
- PINN, DGM and DRM☆19Updated last year
- hPINN: Physics-informed neural networks with hard constraints☆122Updated 3 years ago
- ☆187Updated 3 years ago
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 4 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆75Updated 2 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆64Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆46Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆61Updated last year
- ☆62Updated 5 years ago
- ☆103Updated 3 months ago
- ☆88Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆83Updated 4 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆91Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆48Updated 3 years ago
- Code for "Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions"☆16Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆83Updated last year
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆33Updated 3 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆84Updated 2 years ago
- ☆52Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆136Updated 8 months ago
- ☆128Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆24Updated last year
- ☆155Updated 11 months ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆60Updated 3 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆49Updated 3 years ago
- Physics Informed Neural Networks☆20Updated 4 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆170Updated 2 years ago