A probabilistic risk-based decision framework for structural health monitoring

A variational Bayesian neural network for structural health monitoring and cost-informed decision-making in miter gates

(2020) Manuel A Vega et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Probabilistic active learning: An online framework for structural health monitoring

(2019) L.A. Bull et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A Bayesian non-parametric clustering approach for semi-supervised Structural Health Monitoring

(2018) T.J. Rogers et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Maintenance planning using continuous-state partially observable Markov decision processes and non-linear action models

(2015) Roland Schöbi et al.   Structure and Infrastructure Engineering

A recursive Bayesian approach for fatigue damage prognosis: An experimental validation at the reliability component level

(2013) Maurizio Gobbato et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A Bayesian approach to optimal sensor placement for structural health monitoring with application to active sensing

(2009) Eric B. Flynn et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING