Epistemic AI

DeepSmoke: Deep learning model for smoke detection and segmentation in outdoor environments

Autori: Salman Khan; Salman Khan; Khan Muhammad; Tanveer Hussain; Javier Del Ser; Fabio Cuzzolin; Siddhartha Bhattacharyya; Zahid Akhtar; Victor Hugo C. de Albuquerque
Pubblicato in: Expert Systems with Applications, 2021, Pagina/e 115-125, ISSN 0957-4174
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2021.115125

ROAD-R: the autonomous driving dataset with logical requirements

Autori: Eleonora Giunchiglia, Mihaela Cătălina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz
Pubblicato in: Machine Learning, Numero 112, 2023, Pagina/e 3261-3291, ISSN 0885-6125
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10994-023-06322-z

Fleet planning under demand and fuel price uncertainty using actor–critic reinforcement learning

Autori: Izaak L. Geursen, Bruno F. Santos, Neil Yorke-Smith
Pubblicato in: Journal of Air Transport Management, Numero 109, 2023, Pagina/e 102397, ISSN 0969-6997
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.jairtraman.2023.102397

Most likely heteroscedastic Gaussian process via kernel smoothing

Autori: Ghifari Adam Faza, Nasrulloh R.B.S. Loka, Keivan Shariatmadar, Hans Hallez, David Moens
Pubblicato in: Knowledge-Based Systems, Numero 328, 2026, Pagina/e 114202, ISSN 0950-7051
Editore: Elsevier BV
DOI: 10.1016/j.knosys.2025.114202

Uncertainty measures: A critical survey

Autori: Fabio Cuzzolin
Pubblicato in: Information Fusion, Numero 114, 2024, Pagina/e 102609, ISSN 1566-2535
Editore: Elsevier BV
DOI: 10.1016/j.inffus.2024.102609

Berth planning and real-time disruption recovery: a simulation study for a tidal port

Autori: Jaap-Jan van der Steeg, Menno Oudshoorn, Neil Yorke-Smith
Pubblicato in: Flexible Services and Manufacturing Journal, Numero 35, 2023, Pagina/e 70-110, ISSN 1936-6582
Editore: Springer Pub. Co.,
DOI: 10.1007/s10696-022-09473-8

Enhancing the dependability of autonomous surface vehicles through robustness benchmarking of real-time object detection models

Autori: Yunjia Wang, Zihao Zhang, Kaizheng Wang, Holger Caesar, Jeroen Boydens, Davy Pissoort, Mathias Verbeke
Pubblicato in: Expert Systems with Applications, Numero 296, 2026, Pagina/e 129151, ISSN 0957-4174
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2025.129151

Theory of Mind and Preference Learning at the Interface of Cognitive Science, Neuroscience, and AI: A Review

Autori: Christelle Langley, Bogdan-Ionut Cirstea, Fabio Cuzzolin and Barbara J. Sahakian
Pubblicato in: Frontiers in Artificial Intelligence, Numero April 5 2022, 2022, ISSN 2624-8212
Editore: Frontiers Media S.A.
DOI: 10.3389/frai.2022.778852

ROAD: The ROad event Awareness Dataset for autonomous Driving

Autori: Gurkirt Singh, Stephen Akrigg, Manuele Di Maio, Valentina Fontana, Reza Javanmard Alitappeh, Suman Saha, Kossar Jeddisaravi, Farzad Yousefi, Jacob Culley, Tom Nicholson, Jordan Omokeowa, Salman Khan, Stanislao Grazioso, Andrew Bradley, Giuseppe Di Gironimo, Fabio Cuzzolin
Pubblicato in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ISSN 1939-3539
Editore: IEEE
DOI: 10.1109/tpami.2022.3150906

A Review of Uncertainty Representation and Quantification in Neural Networks

Autori: Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez
Pubblicato in: IEEE Transactions on Pattern Analysis and Machine Intelligence, Numero 48, 2026, Pagina/e 2476-2495, ISSN 0162-8828
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2025.3626645

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

Autori: Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
Pubblicato in: Neural Networks, Numero 185, 2025, Pagina/e 107198, ISSN 0893-6080
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2025.107198

Generalising realisability in statistical learning theory under epistemic uncertainty

Autori: F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2402.14759, Numero 22 Feb 2024, 2024
Editore: Cornell University
DOI: 10.48550/arxiv.2402.14759

Set-based v.s. Distribution-based Representations of Epistemic Uncertainty: A Comparative Study

Autori: K. Wang, Y. Wang, F. Cuzzolin, D. Moens, H. Hallez, S.L. Chau
Pubblicato in: arXiv preprint arXiv:2602.22747, Numero February 26 2026, 2026
Editore: Cornell University
DOI: 10.48550/arxiv.2602.22747

Random-Set Large Language Model

Autori: M. Mubashar, S.K. Manchingal, F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2504.18085, Numero 25 April 2025, 2025
Editore: Cornell University
DOI: 10.48550/arxiv.2504.18085

Epistemic Wrapping for Uncertainty Quantification

Autori: M. Sultana, N. Yorke-Smith, K. Wang, S.K. Manchingal, M. Mubashar, F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2505.02277, Numero 4 May 2025, 2025
Editore: Cornell University
DOI: 10.48550/arxiv.2505.02277

Credal and Interval Deep Evidential Classifications

Autori: M. Caprio, S.K. Manchingal, F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2512.05526, Numero December 5 2025, 2025
Editore: Cornell University
DOI: 10.48550/arxiv.2512.05526

An introduction to optimization under uncertainty -- A short survey

Autori: Shariatmadar, Keivan; Wang, Kaizheng; Hubbard, Calvin R.; Hallez, Hans; Moens, David
Pubblicato in: arXiv report arxiv.2212.00862, Numero 1 Dec 2022, 2022
Editore: Cornell University
DOI: 10.48550/arxiv.2212.00862

Sufficient Decision Proxies For Decision-Focused Learning

Autori: Schutte, N., Veviurko, G., Postek, K., and Yorke-Smith, N.
Pubblicato in: arXiv preprint, Numero May 2025, 2025
Editore: Cornell University
DOI: 10.48550/arxiv.2505.03953

Credal learning theory

Autori: M. Caprio, M. Sultana, E. Elia and F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2402.00957, Numero 2 May 2024, 2024
Editore: Cornell University
DOI: 10.48550/arxiv.2402.00957

Reasoning with random sets: An agenda for the future

Autori: F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2401.09435, Numero 19 Dec 2023, 2024
Editore: Cornell University
DOI: 10.48550/arxiv.2401.09435

The intersection probability: betting with probability intervals

Autori: Fabio Cuzzolin
Pubblicato in: arXiv preprint arxiv.2201.01729, Numero 5 January 2022, 2022
Editore: Cornell University
DOI: 10.48550/arxiv.2201.01729

Uncertainty measures: The big picture

Autori: Fabio Cuzzolin
Pubblicato in: arXiv preprint arxiv.2104.06839, Numero 14 April 2021, 2021
Editore: Cornell University
DOI: 10.48550/arxiv.2104.06839

Direct Interval Propagation Methods using Neural-Network Surrogates for Uncertainty Quantification in Physical Systems Surrogate Model

Autori: Ghifari Adam Faza, Jolan Wauters, Fabio Cuzzolin, Hans Hallez, David Moens
Pubblicato in: SSRN Preprint, Numero November 26 2025, 2025
Editore: Elsevier BV
DOI: 10.2139/ssrn.5812330

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

Autori: Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
Pubblicato in: arXiv preprint arXiv:2401.05043, Numero 2 Feb 2024, 2024
Editore: Cornell University
DOI: 10.48550/arxiv.2401.05043

Epistemic Artificial Intelligence is Essential for Machine Learning Models to Truly 'Know When They Do Not Know'

Autori: S.K. Manchingal, A. Bradley, J.F.P. Kooij, K. Shariatmadar, N. Yorke-Smith, F. Cuzzolin
Pubblicato in: arXiv preprint arXiv:2505.04950, Numero 8 May 2025, 2025
Editore: Cornell University
DOI: 10.48550/arxiv.2505.04950

Path Planning Problem under non-probabilistic Uncertainty

Autori: K. Shariatmadar
Pubblicato in: arXiv preprint arXiv.2212.01388, Numero 1 Dec 2022, 2022
Editore: Cornell University
DOI: 10.48550/arxiv.2212.01388

Vision in adverse weather: Augmentation using CycleGANs with various object detectors for robust perception in autonomous racing

Autori: Izzeddin Teeti, Valentina Musat, Salman Khan, Alexander Rast, Fabio Cuzzolin, Andrew Bradley
Pubblicato in: arXiv preprint arxiv.2201.03246, Numero 11 January 2022, 2022
Editore: Cornell University
DOI: 10.48550/arxiv.2201.03246

Generalisation of Total Uncertainty in AI: A Theoretical Study

Autori: K. Shariatmadar
Pubblicato in: arXiv preprint arXiv.2408.00946, Numero 1 Aug 2024, 2024
Editore: Cornell University
DOI: 10.48550/arxiv.2408.00946

Learning Credal Ensembles via Distributionally Robust Optimization

Autori: K. Wang, G.A. Faza, F. Cuzzolin, S.L. Chau, D. Moens, H. Hallez
Pubblicato in: arXiv preprint arXiv:2602.08470, Numero February 9 2026, 2026
Editore: Cornell University
DOI: 10.48550/arxiv.2602.08470

A geometric approach to conditioning belief functions

Autori: Fabio Cuzzolin
Pubblicato in: arXiv preprint arxiv.2104.10651, Numero 21 April 2021, 2021
Editore: Cornell University
DOI: 10.48550/arxiv.2104.10651

Credal Ensemble Distillation for Uncertainty Quantification

Autori: K. Wang, F. Cuzzolin, D. Moens, H. Hallez
Pubblicato in: 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Numero February 20 2026, 2026
Editore: AAAI Press
DOI: 10.48550/arxiv.2511.13766

On the Estimation of Image-Matching Uncertainty in Visual Place Recognition

Autori: Mubariz Zaffar, Liangliang Nan, Julian F. P. Kooij
Pubblicato in: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Numero 31, 2024, Pagina/e 17743-17753
Editore: IEEE
DOI: 10.1109/cvpr52733.2024.01680

Bayesian Deep Q-Learning via Sequential Monte Carlo

Autori: Pascal Van der Vaart, Matthijs T. J. Spaan, Neil Yorke-Smith
Pubblicato in: 16th European Workshop on Reinforcement Learning (EWRL 2023), Numero 14 Sep 2023, 2023
Editore: EWRL
DOI: 10.5281/zenodo.14245136

Bayesian Model-Free Deep Reinforcement Learning

Autori: Pascal van der Vaart
Pubblicato in: AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, Numero 6 May 2024, 2024, Pagina/e 2782-2784
Editore: IFAAMAS
DOI: 10.5555/3635637.3663285

Incentives for Accurate Energy Predictions: How to Reduce Epistemic Uncertainty

Autori: Roland Saur, Han La Poutré, Neil Yorke-Smith
Pubblicato in: The 15th ACM International Conference on Future and Sustainable Energy Systems, Numero June 4 2024, 2025, Pagina/e 192-202
Editore: ACM
DOI: 10.1145/3632775.3661956

A Hybrid Graph Network for Complex Activity Detection in Video

Autori: Salman Khan, Izzeddin Teeti, Andrew Bradley, Mohamed Elhoseiny, Fabio Cuzzolin
Pubblicato in: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Numero 32, 2024, Pagina/e 6748-6758
Editore: IEEE
DOI: 10.1109/wacv57701.2024.00662

Value Improved Actor Critic Algorithms

Autori: Y. Oren, M. A. Zanger, P. R. van der Vaart, M. M. Çelikok, W. Böhmer, and M. T. J. Spaan
Pubblicato in: The Thirty‑ninth Annual Conference on Neural Information Processing Systems (NeurIPS), Numero 2 December 2025, 2025
Editore: NeurIPS
DOI: 10.48550/arxiv.2406.01423

Diverse Projection Ensembles for Distributional Reinforcement Learning

Autori: Zanger, Moritz A.; Böhmer, Wendelin; Spaan, Matthijs T. J.
Pubblicato in: 16th European Workshop on Reinforcement Learning (EWRL 2023), Numero 14 Sep 2023, 2023
Editore: EWRL
DOI: 10.48550/arxiv.2306.07124

A Unified Evaluation Framework for Epistemic Predictions

Autori: S.K. Manchingal, M. Mubashar, K. Wang, F. Cuzzolin
Pubblicato in: The 28th International Conference on Artificial Intelligence and Statistics, AISTATS 25, Numero 3 May 2025, 2025
Editore: The Proceedings of Machine Learning Research
DOI: 10.48550/arxiv.2501.16912

Bayesian Ensembles for Exploration in Deep Q-Learning

Autori: Pascal Van der Vaart, Neil Yorke-Smith, Matthijs T. J. Spaan
Pubblicato in: Sixteenth Workshop on Adaptive and Learning Agents (ALA 2024), Numero 6 May 2024, 2024, Pagina/e 2528 - 2530
Editore: Adaptive Learning Agents Workshop 2024
DOI: 10.5555/3635637.3663216

Interval Reduced Order Surrogate Modelling Framework for Uncertainty Quantification

Autori: Ghifari A. Faza, Keivan Shariatmadar, Hans Hallez, David Moens
Pubblicato in: AIAA SCITECH 2024 Forum, Numero 4 Jan 2024, 2024
Editore: American Institute of Aeronautics and Astronautics
DOI: 10.2514/6.2024-0387

A generalisation of the Bellman Equation in Epistemic Reinforcement Learning

Autori: K. Shariatmadar, J. Golub, A. Faza, D. Moens
Pubblicato in: XAI workshop, Numero May 23 2024, 2024
Editore: Eindhoven Artificial Intelligence Systems Institute
DOI: 10.5281/zenodo.14217032

Epistemic Deep Learning

Autori: Shireen Kudukkil Manchingal, Fabio Cuzzolin
Pubblicato in: ICML 2022 Workshop on Distribution-Free Uncertainty Quantification, Numero 23 Jul 2022, 2022
Editore: ICML
DOI: 10.48550/arxiv.2206.07609

Diverse Projection Ensembles for Distributional Reinforcement Learning

Autori: Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan
Pubblicato in: The Twelfth International Conference on Learning Representations (ICLR 2024), Numero 7 May 2024, 2024
Editore: ICLR
DOI: 10.5281/zenodo.14236990

How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning

Autori: M. Weltevrede, M. A. Zanger, M. T. J. Spaan, and W. Böhmer.
Pubblicato in: The Thirty‑ninth Annual Conference on Neural Information Processing Systems (NeurIPS),, Numero 2 December 2025, 2025
Editore: NeurIPS
DOI: 10.48550/arxiv.2505.16581

Credal Deep Ensembles for Uncertainty Quantification

Autori: Fabio Cuzzolin, Hans Hallez, Shireen Manchingal, David Moens, Keivan Shariatmadar, Kaizheng Wang
Pubblicato in: Advances in Neural Information Processing Systems 37, Numero 10 December 2024, 2025, Pagina/e 79540-79572
Editore: Neural Information Processing Systems Foundation, Inc. (NeurIPS)
DOI: 10.52202/079017-2525

Uncertainty-Aware Autonomous Vehicles: Predicting the Road Ahead

Autori: S.K. Manchingal, A. Amaritei, M. Gohad, M. Sultana, J.F.P. Kooij, F. Cuzzolin, A. Bradley
Pubblicato in: IEEE International Conference on Robotics & Automation (ICRA 2026), Numero June 1 2026, 2026
Editore: IEEE International Conference on Robotics & Automation (ICRA)
DOI: 10.48550/arxiv.2510.22680

Optimization Under Epistemic Uncertainty With a Focus on Decision-Focused Learning

Autori: Noah Schutte
Pubblicato in: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Numero 3-9 Aug 2024, 2024, Pagina/e 8504-8505
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2024/967

Science of AI - Total Uncertainty in AI

Autori: Keivan Shariatmadar
Pubblicato in: Leuven.AI Workshop, Numero Jun 3 2024, 2024
Editore: KU Leuven
DOI: 10.5281/zenodo.14223938

Credal Wrapper of Model Averaging for Uncertainty Estimation on Out-Of-Distribution Detection

Autori: K. Wang, F. Cuzzolin, K. Shariatmadar, D. Moens, H. Hallez
Pubblicato in: 3th International Conference on Learning Representations (ICLR 2025), Numero 24 April 2025, 2025, ISBN 9798331320850
Editore: International Conference on Learning Representations (ICLR), POD Curran Associates, Inc.
DOI: 10.48550/arxiv.2405.15047

Universal Value-Function Uncertainties

Autori: M.A. Zanger, M. Weltevrede, Y. Oren, P.R. Van der Vaart, C. Horsch, W. Bohmer, M.T.J. Spaan
Pubblicato in: The 14th International Conference on Learning Representations (ICLR 2026), Numero April 23 2026, 2026
Editore: International Conference on Learning Representations (ICLR)
DOI: 10.48550/arxiv.2505.21119

Robust Losses for Decision-Focused Learning

Autori: Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Pubblicato in: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Numero 3-9 Aug 2024, 2024, Pagina/e 4868-4875
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2024/538

Random-Set Convolutional Neural Network (RS-CNN) for Epistemic Deep Learning

Autori: Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin
Pubblicato in: 13th International Conference on Learning Representations (ICLR 2025), Numero 24 April 2025, 2025, ISBN 9798331320850
Editore: International Conference on Learning Representations (ICLR), POD Curran Associates, Inc.
DOI: 10.48550/arxiv.2307.05772

YOLO-Z: Improving small object detection in YOLOv5 for autonomous vehicles

Autori: Aduen Benjumea, Izzeddin Teeti, Fabio Cuzzolin, Andrew Bradley
Pubblicato in: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Numero 23 December 2021, 2021
Editore: IEEE
DOI: 10.48550/arxiv.2112.11798

E-MCTS: Deep Exploration in Model-Based Reinforcement Learning by Planning with Epistemic Uncertainty

Autori: Oren, Yaniv; Spaan, Matthijs T. J.; Böhmer, Wendelin
Pubblicato in: 13th International Conference on Learning Representations (ICLR 2025), Numero 24 April 2025, 2025, ISBN 9798331320850
Editore: International Conference on Learning Representations (ICLR), POD Curran Associates, Inc.
DOI: 10.48550/arxiv.2210.13455

Autori: M.A. Zanger, P.R. Van der Vaart, W. Boehmer, M.T.J. Spaan
Pubblicato in: The 14th International Conference on Learning Representations (ICLR 2026), Numero April 23 2026, 2026
Editore: International Conference on Learning Representations (ICLR)
DOI: 10.48550/arxiv.2503.11339

Credal Learning Theory

Autori: Michele Caprio, Fabio Cuzzolin, Eleni Elia, Maryam Sultana
Pubblicato in: Advances in Neural Information Processing Systems 37, Numero 10 December 2024, 2025, Pagina/e 38665-38694
Editore: Neural Information Processing Systems Foundation, Inc. (NeurIPS)
DOI: 10.52202/079017-1221

Epistemic Bellman Operators

Autori: Pascal R. Van der Vaart, Matthijs T. J. Spaan, Neil Yorke-Smith
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, Numero 39, 2025, Pagina/e 20973-20981, ISSN 2374-3468
Editore: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/aaai.v39i20.35393

Multi-weather city: Adverse weather stacking for autonomous driving

Autori: Valentina Mușat, Ivan Fursa, Paul Newman, Fabio Cuzzolin, Andrew Bradley
Pubblicato in: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Numero 11-17 Oct 2021, 2022
Editore: IEEE
DOI: 10.1109/iccvw54120.2021.00325

Navigating the Waters of Object Detection: Evaluating the Robustness of Real-time Object Detection Models for Autonomous Surface Vehicles

Autori: Yunjia Wang, Kaizheng Wang, Zihao Zhang, Jeroen Boydens, Davy Pissoort, Mathias Verbeke
Pubblicato in: 2024 IEEE Conference on Artificial Intelligence (CAI), Numero June 25 2024, 2024, Pagina/e 985-992
Editore: IEEE
DOI: 10.1109/cai59869.2024.00180

ROAD-R: The Autonomous Driving Dataset with Logical Requirements

Autori: E. Giunchiglia, M. Stoian, S. Khan, F. Cuzzolin and T. Lukasiewicz
Pubblicato in: IJCAI 2022 - Workshop on Artificial Intelligence for Autonomous Driving (AI4AD 2022), Numero 23 Jul 2022, 2022
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.48550/arxiv.2210.01597

Epistemic Uncertainty in Artificial Intelligence

Autori: Fabio Cuzzolin, Maryam Sultana
Pubblicato in: Lecture Notes in Computer Science, Numero 23 Apr 2024, 2024, ISBN 978-3-031-57963-9
Editore: Springer Nature
DOI: 10.1007/978-3-031-57963-9

Uncertainty in Reinforcement Learning and its Application to Scheduling Problems in Manufacturing

Autori: J. Golub, A. Faza, K. Shariatmadar, D. Moens
Pubblicato in: MSc dissertation, 2024
Editore: KU Leuven
DOI: 10.5281/zenodo.14223900

Improving Metaheuristic Efficiency for Stochastic Optimization by Sequential Predictive Sampling

Autori: Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Pubblicato in: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Numero 25 May 2024, 2024, Pagina/e 158-175
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60599-4_10

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