kochlisGit / Physics-Informed-Neural-Network-PINN-Tensorflow
Implementation of a Physics Informed Neural Network (PINN) written in Tensorflow v2, which is capable of solving Partial Differential Equations.
☆14Updated 2 years ago
Alternatives and similar repositories for Physics-Informed-Neural-Network-PINN-Tensorflow:
Users that are interested in Physics-Informed-Neural-Network-PINN-Tensorflow are comparing it to the libraries listed below
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 10 months ago
- Yet another PINN implementation☆19Updated 8 months ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆13Updated 11 months ago
- Transfer learning on PINNs for tracking hemodynamics☆12Updated 7 months ago
- Multifidelity DeepONet☆29Updated last year
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆25Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆22Updated last month
- PINNs for 2D Incompressible Navier-Stokes Equation☆42Updated 9 months ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆46Updated 2 years ago
- Implementing physics informed neural networks (PINN) in PyTorch to solve turbulent flows using the Navier-Stokes equations☆19Updated 9 months ago
- XPINN code written in TensorFlow 2