opaliss / dmd_autoencoder
Enhancing Dynamic Mode Decomposition using Autoencoder Networks.
☆29Updated 3 years ago
Alternatives and similar repositories for dmd_autoencoder:
Users that are interested in dmd_autoencoder are comparing it to the libraries listed below
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆29Updated 2 years ago
- Data-driven reduced order modeling for nonlinear dynamical systems☆60Updated 3 months ago
- Update PDEKoopman code to Tensorflow 2☆23Updated 3 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆55Updated 4 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆46Updated 2 years ago
- Easy Reduced Basis method☆84Updated 3 weeks ago
- A library of tools for computing variants of Dynamic Mode Decomposition☆46Updated 7 years ago
- Modred main repository☆78Updated 3 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆24Updated 3 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
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆72Updated last month
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Updated 4 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆61Updated last year
- Deep Learning for Reduced Order Modelling☆92Updated 3 years ago
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆42Updated 2 years ago
- POD-PINN code and manuscript☆47Updated 3 months ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 2 months ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆67Updated 4 years ago
- Computation of invariant manifolds in high-dimensional mechanics problems☆23Updated last year
- A Python package for spectral proper orthogonal decomposition (SPOD).☆107Updated 3 months ago
- ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis☆51Updated last year
- ☆19Updated 2 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆41Updated 6 years ago
- Companion code for Data-Driven Resolvent Analysis☆18Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆47Updated 3 years ago
- mathLab mirror of Python Dynamic Mode Decomposition☆83Updated 4 months ago
- MATLAB codes for physics-informed dynamic mode decomposition (piDMD)☆137Updated last year
- KTH-FlowAI / beta-Variational-autoencoders-and-transformers-for-reduced-order-modelling-of-fluid-flows☆28Updated last year
- Research/development of physics-informed neural networks for dynamic systems☆18Updated 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