1 citations · 5 across the 22 of their papers we have counts for
4 papers · 2 filters
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar +2
This paper presents an innovative approach, called credal wrapper, to formulating a credal set representation of model averaging for Bayesian neural networks (BNNs) and deep ensemb…
Generalising realisability in statistical learning theory under epistemic uncertainty
Fabio Cuzzolin
The purpose of this paper is to look into how central notions in statistical learning theory, such as realisability, generalise under the assumption that train and test distributio…
Credal Learning Theory
Michele Caprio, Maryam Sultana, Eleni Elia +1
Statistical learning theory is the foundation of machine learning, providing theoretical bounds for the risk of models learned from a (single) training set, assumed to issue from a…
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal +3
Effective uncertainty estimation is becoming increasingly attractive for enhancing the reliability of neural networks. This work presents a novel approach, termed Credal-Set Interv…