kfukami / CNN-SINDy-MLROMLinks
Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.
☆26Updated 4 years ago
Alternatives and similar repositories for CNN-SINDy-MLROM
Users that are interested in CNN-SINDy-MLROM are comparing it to the libraries listed below
Sorting:
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆15Updated 4 years ago
- POD-PINN code and manuscript☆56Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Multi-fidelity reduced-order surrogate modeling☆28Updated 5 months ago
- POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for F…☆32Updated 5 years ago
- ☆22Updated 5 years ago
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆16Updated 4 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆33Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 10 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆25Updated 2 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 3 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated 2 years ago
- Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics☆65Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆38Updated 10 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated 2 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆35Updated 3 years ago
- ☆44Updated 3 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 3 weeks ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Deep Learning of Vortex Induced Vibrations☆99Updated 5 years ago
- ☆40Updated 2 years ago