Epistemic Deep Learning. - Shireen Kudukkil Manchingal; Fabio Cuzzolin (CoRR, 2022)

Random-Set Convolutional Neural Network (RS-CNN) for Epistemic Deep Learning. - Shireen Kudukkil Manchingal; Muhammad Mubashar; Kaizheng Wang; Keivan Shariatmadar; Fabio Cuzzolin (CoRR, 2023)

Credal Deep Ensembles for Uncertainty Quantification. - Kaizheng Wang; Fabio Cuzzolin; Shireen Kudukkil Manchingal; Keivan Shariatmadar; David Moens; Hans Hallez (NeurIPS, 2024)

A Unified Evaluation Framework for Epistemic Predictions. - Shireen Kudukkil Manchingal; Muhammad Mubashar; Kaizheng Wang; Fabio Cuzzolin (AISTATS, 2025)

Random-Set Neural Networks. - Shireen Kudukkil Manchingal; Muhammad Mubashar; Kaizheng Wang; Keivan Shariatmadar; Fabio Cuzzolin (ICLR, 2025)

CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks. - Kaizheng Wang; Keivan Shariatmadar; Shireen Kudukkil Manchingal; Fabio Cuzzolin; David Moens; Hans Hallez (Neural Networks, 2025)

Random-Set Large Language Models. - Muhammad Mubashar; Shireen Kudukkil Manchingal; Fabio Cuzzolin (CoRR, 2025)

Epistemic Wrapping for Uncertainty Quantification. - Maryam Sultana; Neil Yorke-Smith; Kaizheng Wang; Shireen Kudukkil Manchingal; Muhammad Mubashar; Fabio Cuzzolin (CoRR, 2025)

Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know. - Shireen Kudukkil Manchingal; Fabio Cuzzolin (CoRR, 2025)