New DCE paper

Our paper "On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration", led by Antonis Kamariotis (TUM/SMM group at ETHZ), with Luca Sardi (TUM), Iason Papaioannou (TUM), Eleni Chatzi (SMM Chair) and Daniel Straub (TUM), just got published as Open Access in external page Data-Centric Engineering.

In this work, we adapt and investigate off-line (batch) and on-line (recursive) #Bayesian #filters for posterior #uncertainty_quantification of time-invariant parameters. We show that tailored on-line particle filters are competitive alternatives to computationally demanding MCMC-based Bayesian filters.

This paper follows prior work where a library of Bayesian filters for various system identification tasks had been made available (see our tutorial in the external page Journal of Structural Dynamics and our external page GitHub repo).