From the 2 of 17 linked papers with an AI index.
17 papers
Subjective Risk Decomposition: A New View for Uncertainty Quantification
Raghad Alamri, Michele Caprio, Gavin Brown
The paper introduces a framework that derives epistemic and aleatoric uncertainty measures by decomposing a subjective risk defined via a strictly proper loss, unifying many existi…
Quantification of Credal Uncertainty: A Distance-Based Approach
Xabier Gonzalez-Garcia, Siu Lun Chau, Julian Rodemann +6
The paper introduces a distance-based method using Integral Probability Metrics to quantify total, aleatoric, and epistemic uncertainty for credal sets, providing efficient measure…
Hoeffding-Type Concentration Bounds for Exchangeable Random Variables
Nina Maria Gottschling, Michele Caprio
We establish Hoeffding-type concentration inequalities for empirical means of bounded infinitely exchangeable sequences. Using the unique de Finetti mixing measure, we identify the…
Bulk-Calibrated Credal Ambiguity Sets: Fast, Tractable Decision Making under Out-of-Sample Contamination
Mengqi Chen, Thomas B. Berrett, Theodoros Damoulas +1
Distributionally robust optimisation (DRO) minimises the worst-case expected loss over an ambiguity set that can capture distributional shifts in out-of-sample environments. While…
Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features
Michele Caprio, Katerina Papagiannouli, Siu Lun Chau +1
We propose a robust Bayesian formulation of random feature (RF) regression that accounts explicitly for prior and likelihood misspecification via Huber-style contamination sets. St…
Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification
Julian Rodemann, Alexander Marquard, Thomas Augustin +1
Approximate Bayesian inference typically revolves around computing the posterior parameter distribution. In practice, however, the main object of interest is often a model's predic…