Tensor Train Toolbox

Python Dynamic Mode Decomposition

Using data driven numerical methods to perform system identification, model reduction, and design controllers.

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

flowTorch - a Python library for analysis and reduced-order modeling of fluid flows

Non-intrusive Reduced Order Modeling package

For research into the application of Koopman operators at Boston University.

Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

Java Dynamic Mode Decomposition

A Python Implementation of Dynamic Mode Decomposition

This research work is about Limited Data Acquisition for the real life physical experiment of fluid flow across cylinder based on Kernelized Extended Dynamic Mode Decomposition by incorporating Gaussian Random Matrix Theory and Laplacian Kernel Function Hilbert space.

Extended Dynamic Mode Decomposition for system identification from time series data (with dictionary learning, control and streaming options). Diffusion Maps to extract geometric description from data.

Using the dynamic mode decomposition to forcast sales from the m5 competition

Generic Linear Algebra Porting of PyDMD [Ongoing]

Projects for the UW AMATH 582 Computational Methods For Data Analysis class

Solvers to build tmodel approximation of DMD with incomplete information

Predict stocks using DMD, analyze & backtrack performance with Streamlit GUI. Learn ML for stock prediction & analysis with this GitHub repository

This repository contains all the work developed in the context of the Master Thesis dissertation entitled Model Predictive Control for Wake Steering: a Koopman Dynamic Mode Decomposition Approach. The repository includes all developed documentation (dissertation, extended abstract, poster and presentation) source code (MATLAB script and function…

Python tools for non-intrusive reduced order modeling

a little library to help me with things involving Koopman operators