arre-ankit / Physics-Informed-Neural-Networks-PINNs-Links
Physics Informed Neural Networks (PINNs) is a machine learning technique that incorporates physical laws and constraints into the neural network training process for solving partial differential equations (PDEs) in various fields of science and engineering, including solid mechanics.
☆12Updated last year
Alternatives and similar repositories for Physics-Informed-Neural-Networks-PINNs-
Users that are interested in Physics-Informed-Neural-Networks-PINNs- are comparing it to the libraries listed below
Sorting:
- Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network☆19Updated 3 weeks ago
- A Jupyter Notebook implementation of Physics-informed neural network to solve solid mechanics problem.☆24Updated 2 years ago
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Updated 3 years ago
- Physics-Informed Super-Resolution☆10Updated 2 years ago
- This is the official implementation of "Deep Fuzzy Physics-Informed Neural Networks for Forward and Inverse PDE Problems" (Neural Network…☆27Updated 2 months ago
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago
- Code of the publication "Physics informed neural networks for continuum micromechanics" published in https://doi.org/10.1016/j.cma.2022.1…☆19Updated 3 years ago
- ☆13Updated 2 years ago
- Use of Turbulence Model (Spalart-Allmaras) with PINNs for mean flow reconstruction☆12Updated last year
- Implementation of physics-informed PointNet (PIPN) for weakly-supervised learning of incompressible flows and thermal fields on irregular…☆13Updated 5 months ago
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆20Updated last year
- Physics-informed radial basis network☆33Updated last year
- This repository implements Physics-Informed Neural Networks (PINNs) for slope stability analysis based on the Mohr-Coulomb failure criter…☆11Updated 4 months ago
- Multi-head attention network for airfoil flow field prediction☆17Updated 3 years ago
- Soving heat transfer problems using PINN with tf2.0☆20Updated 4 years ago
- Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material proper…☆23Updated 2 years ago
- FEM enhanced neural network☆20Updated 3 years ago
- Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet☆14Updated last year
- ☆20Updated last year
- ☆44Updated 3 years ago
- ☆27Updated last year
- Physics-Informed Neural Network (PINN) for Solving Direct and Inverse Heat Conduction Problems☆13Updated 3 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Updated 2 years ago
- ☆14Updated last year
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆15Updated last year
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- ☆12Updated 2 weeks ago
- Numerical schemes for the Cahn-Hilliard equation.☆19Updated 8 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆38Updated 2 years ago
- This project is divided in a two parts. In first study, Lame parameters are identified using tanh activation function. After that, six a…☆13Updated 3 years ago