Abstract: Predictive maintenance is essential for ensuring the reliability and efficiency of wind energy systems. Traditional deep learning models for sensor fault detection rely solely on data-driven ...

Abstract: This paper investigates the viability of using the dynamic Bayesian Network framework as a tool to classify heart beats in long term ECG records. A Decision Support System composed by two ...

We investigate several reinforcement learning algorithms on three Bayesian experimental design problems. Performance is measured by each agent's training time and generalisability to various ...

In this work, we develop a new framework for designing experiments that are robust to model misspecification through generalised Bayesian inference. This repository contains the files needed to ...