From the 2 of 5 linked papers with an AI index.
5 papers
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
The paper introduces a recursive filtering method that jointly estimates glucose levels and model parameters in real time for type‑1 diabetes, using a Rao‑Blackwellized Stein Varia…
Learning reduced-order latent linear models for Kalman filtering of nonlinear systems
Manas Mejari, Milad Banitalebi Dehkordi, Dario Piga
The paper introduces an end-to-end learning framework that jointly trains an autoencoder and a reduced-order linear model to perform Kalman filtering directly in a low-dimensional…
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 Rao-Blackwellization techniqu…
Learning Low-Dimensional Embeddings for Black-Box Optimization
Riccardo Busetto, Manas Mejari, Marco Forgione +2
When gradient-based methods are impractical, black-box optimization (BBO) provides a valuable alternative. However, BBO often struggles with high-dimensional problems and limited t…
Bias correction and instrumental variables for direct data-driven model-reference control
Manas Mejari, Valentina Breschi, Simone Formentin +1
Managing noisy data is a central challenge in direct data-driven control design. We propose an approach for synthesizing model-reference controllers for linear time-invariant (LTI)…