53 citations · 151 across the 36 of their papers we have counts for
3 papers · 1 filter
Learning stochasticity: a nonparametric framework for intrinsic noise estimation
Gianluigi Pillonetto, Alberto Giaretta, Mauro Bisiacco
Understanding the principles that govern dynamical systems is a central challenge across many scientific domains, including biology and ecology. Incomplete knowledge of nonlinear i…
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…
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…