Panda000001 / PINN-PODLinks
This repository contains the source code for the research presented in the paper "Exploring hidden flow structures from sparse data through deep-learning-strengthened proper orthogonal decomposition"
☆11Updated last year
Alternatives and similar repositories for PINN-POD
Users that are interested in PINN-POD are comparing it to the libraries listed below
Sorting:
- POD-PINN code and manuscript☆51Updated 6 months ago
- ☆25Updated 4 months ago
- A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation☆28Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆31Updated 3 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- PINNs-MPF is a comprehensive framework designed for simulating interface dynamics using Physics-Informed Neural Networks (PINNs). Leverag…☆13Updated last month
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆32Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 4 months ago
- ☆10Updated last year
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated last year
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 4 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆15Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆32Updated 2 years ago
- A convolutional neural network for drag prediction in laminar flows☆14Updated 4 years ago
- Data preprocess method on Physics-informed neural networks☆15Updated 3 months ago
- Multifidelity DeepONet☆33Updated last year
- ☆17Updated 7 months ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆26Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆61Updated 3 weeks ago
- ☆8Updated 6 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- Deep finite volume method☆21Updated 11 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆28Updated last year
- Physics-guided neural network framework for elastic plates☆39Updated 3 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆22Updated 2 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆78Updated 2 years ago
- ☆38Updated 3 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆24Updated last year
- Physics-Informed Neural Network☆84Updated last year
- Yet another PINN implementation☆20Updated 11 months ago