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cs.LG2025
On-line learning of dynamic systems: sparse regression meets Kalman filtering
Gianluigi Pillonetto, Akram Yazdani, Aleksandr Aravkin
Learning governing equations from data is central to understanding the behavior of physical systems across diverse scientific disciplines, including physics, biology, and engineeri…
cs.LG2025
Sparse and nonparametric estimation of equations governing dynamical systems with applications to biology
G. Pillonetto, A. Giaretta, A. Aravkin +2
Data-driven discovery of model equations is a powerful approach for understanding the behavior of dynamical systems in many scientific fields. In particular, the ability to learn m…
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…