Surrogate-model-assisted uncertainty treatment practices have been the subject of
increasing attention and investigations in recent decades for many symmetrical engineering …

This article reviews the current knowledge and recent advancements in computational
modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms …

As a state-of-the-art green façade technology, building-integrated microalgae bioreactor has
the potential to reduce buildings' carbon footprint and energy consumption. The present …

Importance sampling (IS) is a Monte Carlo technique for the approximation of intractable
distributions and integrals with respect to them. The origin of IS dates from the early 1950s …

This work introduces a comprehensive approach to assess the sensitivity of model outputs to
changes in parameter values, constrained by the combination of prior beliefs and data. This …

In this paper we address the problem of performing Bayesian inference for the parameters of
a nonlinear multioutput model and the covariance matrix of the different output signals. We …

The Bayesian model updating approach has attracted much attention by providing the most
probable values (MPVs) of physical parameters and their uncertainties. However, the …

Taking inspiration from linguistics, the communications theoretical community has recently
shown a significant recent interest in pragmatic, or goal-oriented, communication. In this …

Abstract In econometrics, Autoregressive Conditional Duration (ACD) models use high-
frequency economic or financial duration data, which mostly exhibit irregular time intervals …

State-space models (SSM) are central to describe time-varying complex systems in
countless signal processing applications such as remote sensing, networks, biomedicine …