GaloisInc/dlkoopman
A general-purpose Python package for Koopman theory using deep learning.
This project helps scientists and engineers predict the future behavior of complex systems. It takes time-series data from any physical or engineered system (like an aircraft's pressure over time or a pendulum's swing) and uses deep learning to create a simplified, linear model. The output is a highly accurate prediction of how the system will evolve under new conditions or at future points in time.
120 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to understand and accurately predict the behavior of complex, non-linear dynamical systems based on sampled data.
Not ideal if your system is already well-described by linear equations or if you require extremely fast, real-time predictions without a training phase.
Stars
120
Forks
15
Language
Python
License
MIT
Category
Last pushed
Sep 24, 2025
Commits (30d)
0
Dependencies
6
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