3 papers
eess.SY2026
A Unified Bayesian Framework for Data-Driven Smoothing, Prediction, and Control
Mingzhou Yin, Andrea Iannelli, Seyed Ali Nazari +1
Extending data-driven algorithms based on Willems' fundamental lemma to stochastic data often requires empirical and customized workarounds. This work presents a unified Bayesian f…
eess.SY2026
Data-Driven Prediction and Control of Hammerstein-Wiener Systems with Implicit Gaussian Processes
Mingzhou Yin, Matthias A. Müller
This work investigates data-driven prediction and control of Hammerstein-Wiener systems using physics-informed Gaussian process (GP) models that encode the block-oriented model str…
eess.SY2025
Low-Rank Matrix Regression via Least-Angle Regression
Mingzhou Yin, Matthias A. Müller
Low-rank matrix regression is a fundamental problem in data science with various applications in systems and control. Nuclear norm regularization has been widely applied to solve t…