Abstract: This article considers the application of variational Bayesian methods to joint recursive estimation of the dynamic state and the time-varying measurement noise parameters in linear state ...

Bayesian predictive density estimation represents a cornerstone of modern statistical inference by integrating prior knowledge with observed data to produce a predictive distribution for future ...

Abstract: In complex and dynamic maritime environments, the uncertain navigation intent of target ships (TS) poses a significant challenge for the collision avoidance strategies of unmanned surface ...

We will keep our notes and code on dealing with censored variables in Bayesian models in this repo. My initial idea for this is that we can basically treat each worked out example or section that we ...

Fault detection and diagnosis (FDD) is essential for maintaining safety and preventing hazardous situations in industrial process control. Effective fault diagnosis allows for the timely detection and ...