Credal networks generalize Bayesian networks to allow for imprecision in probability values.
This paper reviews the main results on credal networks under strong independence, as …

The estimation of the conditional failure rate (CFR) of an overhead transmission line (OTL) is
essential for power system operational reliability assessment. It is hard to predict the CFR …

Transformer fault diagnosis is important for improving the operational reliability of power
systems. Despite great efforts to enhance the accuracy of fault diagnosis, the precise …

This short paper discusses the contributions made to the featured section on Low Quality
Data. We further refine the distinction between the ontic and epistemic views of imprecise …

This paper presents a general framework for learning with imprecise probabilities, consisting
of a hierarchical approach with two sets of parameters. In the top set we have imprecise …

This article introduces a novel method for asset and option trading in a binomial scenario.
This method uses nonparametric predictive inference (NPI), a statistical methodology within …

Bayesian model averaging (BMA) is the state of the art approach for overcoming model
uncertainty. Yet, especially on small data sets, the results yielded by BMA might be sensitive …

The problem of learning from categorical data is commonly known in many fields. Besides
the principal complexity arising from non-correspondence between latent and manifest …

In this paper, the authors address the issue of updating in a Bayesian framework, the
possibilistic representation of the epistemically uncertain parameters of (aleatory) probability …

Wilcox proposed an argument against imprecise probabilities and for the principle of
indifference based on a thought experiment where he argues that it is very intuitive to feel …