kfukami / CNN-SINDy-MLROM
Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.
☆24Updated 3 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
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆13Updated 3 years ago
- POD-PINN code and manuscript☆47Updated 3 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…☆29Updated 4 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆29Updated last year
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆9Updated last year
- 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…☆15Updated 3 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆16Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆31Updated 7 months ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆33Updated 9 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆29Updated 2 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Updated 4 years ago
- Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow …☆17Updated 3 years ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆17Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 2 months ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆22Updated last year
- Physics-informed neural networks for highly compressible flows 🧠🌊☆22Updated last year
- Standardized Non-Intrusive Reduced Order Modeling☆12Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆59Updated last year
- Python tools for non-intrusive reduced order modeling☆18Updated 6 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆19Updated last year
- Multifidelity DeepONet☆27Updated last year
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- Numerical tool for Construction of Reduced-order models for fluid flows.☆30Updated 4 years ago
- Companion code for Data-Driven Resolvent Analysis☆18Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆47Updated 4 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆24Updated 3 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆39Updated 9 months ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated last year