Jianxun-Wang / phygeonet
PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain
☆80Updated 3 years ago
Related projects: ⓘ
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆69Updated 2 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆55Updated last year
- ☆91Updated 2 months ago
- ☆47Updated last year
- POD-PINN code and manuscript☆44Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆76Updated last year
- Physics-informed neural networks for two-phase flow problems☆45Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆43Updated 2 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆26Updated 4 months ago
- Deep learning library for solving differential equations on top of PyTorch.☆59Updated 4 years ago
- PINN in solving Navier–Stokes equation☆71Updated 4 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆15Updated 2 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆48Updated last year
- DeepONet extrapolation☆20Updated last year
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆83Updated 2 years ago
- ☆82Updated 2 years ago
- physics-informed neural network for elastodynamics problem☆112Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆26Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆118Updated 4 months ago
- ☆113Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆59Updated last year
- gPINN: Gradient-enhanced physics-informed neural networks☆72Updated 2 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆46Updated 3 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆15Updated 3 months ago
- Physics Informed Neural Networks: a starting step for CFD specialists☆26Updated 2 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆115Updated 4 years ago
- Deep Learning of Vortex Induced Vibrations☆84Updated 4 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆53Updated 5 months ago
- ☆60Updated 5 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆43Updated 2 years ago