4 papers
Unsupervised multi-scale diagnostics
Karl Lapo, Sara M. Ichinaga, Nathan Kutz
The unsupervised and principled diagnosis of multi-scale data is a fundamental obstacle in modern scientific problems from, for instance, weather and climate prediction, neurology,…
Learning Nonlinear Dynamics Using Kalman Smoothing
Jacob Stevens-Haas, Yash Bhangale, Aleksandr Aravkin +1
Identifying Ordinary Differential Equations (ODEs) from measurement data requires both fitting the dynamics and assimilating, either implicitly or explicitly, the measurement data.…
Spatiotemporal k-means
Olga Dorabiala, Devavrat Vivek Dabke, Jennifer Webster +2
Spatiotemporal data is increasingly available due to emerging sensor and data acquisition technologies that track moving objects. Spatiotemporal clustering addresses the need to ef…
Nonlinear control of networked dynamical systems
Megan Morrison, J. Nathan Kutz
We develop a principled mathematical framework for controlling nonlinear, networked dynamical systems. Our method integrates dimensionality reduction, bifurcation theory and emergi…