MinglangYin / PyTorchTutorial
Examplary code for NN, MFNN, DynNet, PINNs and CNN
☆42Updated 3 years ago
Related projects: ⓘ
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆46Updated 3 years ago
- POD-PINN code and manuscript☆44Updated 3 years ago
- Physics Informed Neural Networks (based on Raissi et al) extended to three dimensions on the heat diffusion equations☆15Updated 2 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆48Updated last year
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 4 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆48Updated 3 years ago
- Basic implementation of physics-informed neural network with pytorch.☆40Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆69Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆76Updated last year
- Physics Informed Neural Networks: a starting step for CFD specialists☆26Updated 2 years ago
- DeepXDE and PINN☆72Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆43Updated 2 years ago
- PINN in solving Navier–Stokes equation☆71Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆29Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆53Updated 5 months ago
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆22Updated last year
- Contains implementation of PINN using Tensorflow 2.4.0☆14Updated last year
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆94Updated 5 months ago
- Pytorch implementation of Bayesian physics-informed neural networks☆33Updated 3 years ago
- Boosting the training of physics informed neural networks with transfer learning☆24Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆23Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆42Updated 4 years ago
- Physics-informed neural networks for two-phase flow problems☆45Updated last year
- Deep learning library for solving differential equations on top of PyTorch.☆59Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆80Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆55Updated last year
- ☆47Updated last year
- ☆12Updated 6 months 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
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆59Updated last year