rsmath / dt-pinnLinks
Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations
☆27Updated 2 years ago
Alternatives and similar repositories for dt-pinn
Users that are interested in dt-pinn are comparing it to the libraries listed below
Sorting:
- Physics-informed radial basis network☆30Updated last year
- Multifidelity DeepONet☆34Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆29Updated last year
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆55Updated 3 years ago
- POD-PINN code and manuscript☆52Updated 8 months ago
- MIONet: Learning multiple-input operators via tensor product☆34Updated 2 years ago
- ☆33Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆88Updated last year
- Physics-guided neural network framework for elastic plates☆42Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆86Updated 4 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆11Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆39Updated 10 months ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- ☆30Updated 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…☆65Updated last month
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆25Updated 3 years ago
- ☆29Updated 2 years ago
- ☆19Updated last year
- ☆39Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆71Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆80Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆22Updated last year
- Physics-informed neural networks for identifying material properties in solid mechanics☆21Updated 2 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆23Updated 2 years ago
- This repository includes the implementation of the Physics Informed Neural Network and The Deep Energy Method on 1D, 2D boundary value an…☆15Updated 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…☆25Updated 5 months ago
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago