4 papers
A Bayesian framework for multilevel data under model mis-specification
Widemberg S. Nobre, David A. Stephens, Alexandra M. Schmidt +1
We propose a Bayesian framework for uncertainty quantification from the perspective that the working model is mis-specified in settings of a multilevel data-generating process. We…
Bootstrap validity in Bayesian semi-parametric models
Magid Sabbagh, David A. Stephens
We discuss Bayesian inference on a low-dimensional targeted parameter in the presence of possibly highly complex nuisance components within the semi-parametric inference framework…
Semi-parametric Bayesian inference under Neyman orthogonality
Magid Sabbagh, David A. Stephens
The validity of two-step or plug-in inference methods is questioned in the Bayesian framework. We study semi-parametric models where the plug-in of a non-parametrically modelled nu…
Not Just How Much, But Where: Decomposing Epistemic Uncertainty into Per-Class Contributions
Mame Diarra Toure, David A. Stephens
In safety-critical classification, the cost of failure is often asymmetric, yet Bayesian deep learning summarises epistemic uncertainty with a single scalar, mutual information (MI…