3 papers
math.DS2024
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,…
math.DS2024
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.…
cs.LG2024
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…