eshaghi-ms / VINOLinks
Variational Physic-informed Neural Operator (VINO) for Learning Partial Differential Equations
☆25Updated 3 months ago
Alternatives and similar repositories for VINO
Users that are interested in VINO are comparing it to the libraries listed below
Sorting:
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆44Updated last year
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆38Updated 2 years ago
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆71Updated 7 months ago
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago
- Soving heat transfer problems using PINN with tf2.0☆20Updated 4 years ago
- Physics-informed radial basis network☆34Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- PINNs for 2D Incompressible Navier-Stokes Equation☆57Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆28Updated 11 months ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆57Updated last week
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- ☆33Updated 11 months ago
- Use of Turbulence Model (Spalart-Allmaras) with PINNs for mean flow reconstruction☆12Updated last year
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆33Updated 2 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆59Updated last year
- Multi-fidelity reduced-order surrogate modeling☆29Updated 6 months ago
- ☆44Updated 3 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Updated 3 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆37Updated 3 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- POD-PINN code and manuscript☆57Updated last year
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆22Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆87Updated 4 months ago
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆20Updated last year
- ☆15Updated 2 years ago
- ☆15Updated 2 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆32Updated 2 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆18Updated last year