CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks

28 January 2025

Papers citing "CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks"

10 / 10 papers shown

Title
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know Shireen Kudukkil Manchingal Fabio Cuzzolin 39 0 0 08 May 2025
Random-Set Large Language Models Muhammad Mubashar Shireen Kudukkil Manchingal Fabio Cuzzolin 61 0 0 25 Apr 2025
A calibration test for evaluating set-based epistemic uncertainty representations Mira Jürgens Thomas Mortier Eyke Hüllermeier Viktor Bengs Willem Waegeman 26 0 0 22 Feb 2025
A Unified Evaluation Framework for Epistemic Predictions Shireen Kudukkil Manchingal Muhammad Mubashar Kaizheng Wang Fabio Cuzzolin UQCV 51 2 0 28 Jan 2025
Generalisation of Total Uncertainty in AI: A Theoretical Study Sari Masri AI4CE 23 0 0 01 Aug 2024
Generalising realisability in statistical learning theory under epistemic uncertainty Fabio Cuzzolin CML 21 0 0 22 Feb 2024
Credal Learning Theory Michele Caprio Maryam Sultana Eleni Elia Fabio Cuzzolin FedML 34 4 0 01 Feb 2024
Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference M. Shaker Eyke Hüllermeier UD UQCV PER BDL 211 16 0 21 Jul 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 4,940 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 243 9,042 0 06 Jun 2015