Learning-based augmentation of first-principle models: A linear fractional representation-based approach
(ArXiv version)
Port-hamiltonian neural networks with output error noise models
Deep Learning for Continuous-Time Nonlinear System Identification
Detecting and Quantifying Nonlinearity in Dynamic Networks
Nonparametric Data-Driven Modeling of Linear Systems
Survey on Block-Oriented Identification
Please consult my Google Scholar profile or the university repository through the links below for a more detailed publication overview.