Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

A complete, hardware-ready Python package for Koopman-based Linear Model Predictive Control (LMPC), delivering real-time trajectory tracking for quadrotors using analytical Koopman lifting (no training data required)

This document explains the implementation of the Koopman Operator in conjunction with Model Predictive Control (MPC) to control a nonlinear system.

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.

A repository for an online adaptive Koopman algorithm described for the paper titled "Adaptive Koopman Architectures for Control of Complex Nonlinear Systems".

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…

My Master Thesis in the area of Data-Driven Control Engineering

Official repository for CoRL 2025 Paper: 'KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning' by Li et al. from GRASP Lab, UPenn

This code can be used to reproduce the results in our paper ``Extended Kalman filter---Koopman operator for tractable stochastic optimal control'.

Koopman-Assisted Reinforcement Learning

Scaling Law of Neural Koopman Operators

A framework for data-driven modeling and analysis of granular materials in the strongly nonlinear regime using the modern Koopman theory

Official code for the IEEE SPL paper "Stabilizing RED using the Koopman Operator (SKOOP-RED)." Includes implementations, demos, and scripts to reproduce results and plots.

koopman operator examples

Adaptive deep Koopman predictive control for mitigating traffic oscillations in mixed CAV/HDV traffic, with pretrained checkpoint and reproducible simulation code.

Koope Is an ultra-fast, local offline Rust-based LLM runner for Windows that executes GGUF models under 100MB of RAM using native Win32 memory locks and Port-Hamiltonian stability. prompt injection (OPHIK), and Koopman Operator Theory to guarantee instant, hallucination-free local AI execution.

Typed audit calculus for scientific transfers, with formal fixtures, claim ledgers, and reproducibility gates.

Research presentation on Koopman Operator Theory, DMD, EDMD applied for JUICE and pendulum.

A Graph Dynamical Neural Network Approach for Decoding Dynamical States in Ferroelectrics.

Stability-guaranteed network for learning Complex dynamical systems