17 citations · 32 across the 20 of their papers we have counts for
5 papers · 1 filter
Joint State-Parameter Inference Enhances Estimation Performance in Model-Based Digital Therapeutics for Type 1 Diabetes
Milad Banitalebi Dehkordi, Vihangkumar V. Naik, Manas Mejari +2
Blood glucose estimation is the cornerstone of model-based decision support (DS) and Automated Insulin Delivery (AID) systems. Control systems that rely on physiologic/compartmenta…
Variational meta-learning inference for low dimensional neural system identification
Matteo Rufolo, Dario Piga, Marco Forgione
Deep learning has proven highly effective for nonlinear system identification, but heavily parameterized neural networks are prone to overfitting in low-data regimes and lack relia…
Learning reduced-order latent linear models for Kalman filtering of nonlinear systems
Manas Mejari, Milad Banitalebi Dehkordi, Dario Piga
We propose a filtering-oriented end-to-end learning framework to identify reduced-order models explicitly tailored for state estimation in high-dimensional nonlinear systems. An au…
ASIA: an Autonomous System Identification Agent
Dario Piga, Marco Forgione
Over the years, research in system identification has provided a rich set of methods for learning dynamical models, together with well-established theoretical guarantees. In practi…
Rao-Blackwellized Stein Gradient Descent for Joint State-Parameter Estimation
Milad Banitalebi Dehkordi, Manas Mejari, Dario Piga
We present a filtering framework for online joint state estimation and parameter identification in nonlinear, time-varying systems. The algorithm uses a Rao-Blackwellization techni…