Epistemic AI

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

Autores: Salman Khan; Salman Khan; Khan Muhammad; Tanveer Hussain; Javier Del Ser; Fabio Cuzzolin; Siddhartha Bhattacharyya; Zahid Akhtar; Victor Hugo C. de Albuquerque
Publicado en: Expert Systems with Applications, 2021, Página(s) 115-125, ISSN 0957-4174
Editor: Pergamon Press Ltd.
DOI: 10.1016/j.eswa.2021.115125

ROAD-R: the autonomous driving dataset with logical requirements

Autores: Eleonora Giunchiglia, Mihaela Cătălina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz
Publicado en: Machine Learning, Edición 112, 2023, Página(s) 3261-3291, ISSN 0885-6125
Editor: Kluwer Academic Publishers
DOI: 10.1007/s10994-023-06322-z

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

Autores: Izaak L. Geursen, Bruno F. Santos, Neil Yorke-Smith
Publicado en: Journal of Air Transport Management, Edición 109, 2023, Página(s) 102397, ISSN 0969-6997
Editor: Pergamon Press Ltd.
DOI: 10.1016/j.jairtraman.2023.102397

Most likely heteroscedastic Gaussian process via kernel smoothing

Autores: Ghifari Adam Faza, Nasrulloh R.B.S. Loka, Keivan Shariatmadar, Hans Hallez, David Moens
Publicado en: Knowledge-Based Systems, Edición 328, 2026, Página(s) 114202, ISSN 0950-7051
Editor: Elsevier BV
DOI: 10.1016/j.knosys.2025.114202

Uncertainty measures: A critical survey

Autores: Fabio Cuzzolin
Publicado en: Information Fusion, Edición 114, 2024, Página(s) 102609, ISSN 1566-2535
Editor: Elsevier BV
DOI: 10.1016/j.inffus.2024.102609

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

Autores: Jaap-Jan van der Steeg, Menno Oudshoorn, Neil Yorke-Smith
Publicado en: Flexible Services and Manufacturing Journal, Edición 35, 2023, Página(s) 70-110, ISSN 1936-6582
Editor: 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

Autores: Yunjia Wang, Zihao Zhang, Kaizheng Wang, Holger Caesar, Jeroen Boydens, Davy Pissoort, Mathias Verbeke
Publicado en: Expert Systems with Applications, Edición 296, 2026, Página(s) 129151, ISSN 0957-4174
Editor: 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

Autores: Christelle Langley, Bogdan-Ionut Cirstea, Fabio Cuzzolin and Barbara J. Sahakian
Publicado en: Frontiers in Artificial Intelligence, Edición April 5 2022, 2022, ISSN 2624-8212
Editor: Frontiers Media S.A.
DOI: 10.3389/frai.2022.778852

ROAD: The ROad event Awareness Dataset for autonomous Driving

Autores: 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
Publicado en: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ISSN 1939-3539
Editor: IEEE
DOI: 10.1109/tpami.2022.3150906

A Review of Uncertainty Representation and Quantification in Neural Networks

Autores: Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez
Publicado en: IEEE Transactions on Pattern Analysis and Machine Intelligence, Edición 48, 2026, Página(s) 2476-2495, ISSN 0162-8828
Editor: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpami.2025.3626645

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

Autores: Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
Publicado en: Neural Networks, Edición 185, 2025, Página(s) 107198, ISSN 0893-6080
Editor: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2025.107198

Generalising realisability in statistical learning theory under epistemic uncertainty

Autores: F. Cuzzolin
Publicado en: arXiv preprint arXiv:2402.14759, Edición 22 Feb 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2402.14759

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

Autores: K. Wang, Y. Wang, F. Cuzzolin, D. Moens, H. Hallez, S.L. Chau
Publicado en: arXiv preprint arXiv:2602.22747, Edición February 26 2026, 2026
Editor: Cornell University
DOI: 10.48550/arxiv.2602.22747

Random-Set Large Language Model

Autores: M. Mubashar, S.K. Manchingal, F. Cuzzolin
Publicado en: arXiv preprint arXiv:2504.18085, Edición 25 April 2025, 2025
Editor: Cornell University
DOI: 10.48550/arxiv.2504.18085

Epistemic Wrapping for Uncertainty Quantification

Autores: M. Sultana, N. Yorke-Smith, K. Wang, S.K. Manchingal, M. Mubashar, F. Cuzzolin
Publicado en: arXiv preprint arXiv:2505.02277, Edición 4 May 2025, 2025
Editor: Cornell University
DOI: 10.48550/arxiv.2505.02277

Credal and Interval Deep Evidential Classifications

Autores: M. Caprio, S.K. Manchingal, F. Cuzzolin
Publicado en: arXiv preprint arXiv:2512.05526, Edición December 5 2025, 2025
Editor: Cornell University
DOI: 10.48550/arxiv.2512.05526

An introduction to optimization under uncertainty -- A short survey

Autores: Shariatmadar, Keivan; Wang, Kaizheng; Hubbard, Calvin R.; Hallez, Hans; Moens, David
Publicado en: arXiv report arxiv.2212.00862, Edición 1 Dec 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2212.00862

Sufficient Decision Proxies For Decision-Focused Learning

Autores: Schutte, N., Veviurko, G., Postek, K., and Yorke-Smith, N.
Publicado en: arXiv preprint, Edición May 2025, 2025
Editor: Cornell University
DOI: 10.48550/arxiv.2505.03953

Credal learning theory

Autores: M. Caprio, M. Sultana, E. Elia and F. Cuzzolin
Publicado en: arXiv preprint arXiv:2402.00957, Edición 2 May 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2402.00957

Reasoning with random sets: An agenda for the future

Autores: F. Cuzzolin
Publicado en: arXiv preprint arXiv:2401.09435, Edición 19 Dec 2023, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2401.09435

The intersection probability: betting with probability intervals

Autores: Fabio Cuzzolin
Publicado en: arXiv preprint arxiv.2201.01729, Edición 5 January 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2201.01729

Uncertainty measures: The big picture

Autores: Fabio Cuzzolin
Publicado en: arXiv preprint arxiv.2104.06839, Edición 14 April 2021, 2021
Editor: Cornell University
DOI: 10.48550/arxiv.2104.06839

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

Autores: Ghifari Adam Faza, Jolan Wauters, Fabio Cuzzolin, Hans Hallez, David Moens
Publicado en: SSRN Preprint, Edición November 26 2025, 2025
Editor: Elsevier BV
DOI: 10.2139/ssrn.5812330

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

Autores: Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
Publicado en: arXiv preprint arXiv:2401.05043, Edición 2 Feb 2024, 2024
Editor: 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'

Autores: S.K. Manchingal, A. Bradley, J.F.P. Kooij, K. Shariatmadar, N. Yorke-Smith, F. Cuzzolin
Publicado en: arXiv preprint arXiv:2505.04950, Edición 8 May 2025, 2025
Editor: Cornell University
DOI: 10.48550/arxiv.2505.04950

Path Planning Problem under non-probabilistic Uncertainty

Autores: K. Shariatmadar
Publicado en: arXiv preprint arXiv.2212.01388, Edición 1 Dec 2022, 2022
Editor: 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

Autores: Izzeddin Teeti, Valentina Musat, Salman Khan, Alexander Rast, Fabio Cuzzolin, Andrew Bradley
Publicado en: arXiv preprint arxiv.2201.03246, Edición 11 January 2022, 2022
Editor: Cornell University
DOI: 10.48550/arxiv.2201.03246

Generalisation of Total Uncertainty in AI: A Theoretical Study

Autores: K. Shariatmadar
Publicado en: arXiv preprint arXiv.2408.00946, Edición 1 Aug 2024, 2024
Editor: Cornell University
DOI: 10.48550/arxiv.2408.00946

Learning Credal Ensembles via Distributionally Robust Optimization

Autores: K. Wang, G.A. Faza, F. Cuzzolin, S.L. Chau, D. Moens, H. Hallez
Publicado en: arXiv preprint arXiv:2602.08470, Edición February 9 2026, 2026
Editor: Cornell University
DOI: 10.48550/arxiv.2602.08470

A geometric approach to conditioning belief functions

Autores: Fabio Cuzzolin
Publicado en: arXiv preprint arxiv.2104.10651, Edición 21 April 2021, 2021
Editor: Cornell University
DOI: 10.48550/arxiv.2104.10651

Credal Ensemble Distillation for Uncertainty Quantification

Autores: K. Wang, F. Cuzzolin, D. Moens, H. Hallez
Publicado en: 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026), Edición February 20 2026, 2026
Editor: AAAI Press
DOI: 10.48550/arxiv.2511.13766

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

Autores: Mubariz Zaffar, Liangliang Nan, Julian F. P. Kooij
Publicado en: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Edición 31, 2024, Página(s) 17743-17753
Editor: IEEE
DOI: 10.1109/cvpr52733.2024.01680

Bayesian Deep Q-Learning via Sequential Monte Carlo

Autores: Pascal Van der Vaart, Matthijs T. J. Spaan, Neil Yorke-Smith
Publicado en: 16th European Workshop on Reinforcement Learning (EWRL 2023), Edición 14 Sep 2023, 2023
Editor: EWRL
DOI: 10.5281/zenodo.14245136

Bayesian Model-Free Deep Reinforcement Learning

Autores: Pascal van der Vaart
Publicado en: AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, Edición 6 May 2024, 2024, Página(s) 2782-2784
Editor: IFAAMAS
DOI: 10.5555/3635637.3663285

Incentives for Accurate Energy Predictions: How to Reduce Epistemic Uncertainty

Autores: Roland Saur, Han La Poutré, Neil Yorke-Smith
Publicado en: The 15th ACM International Conference on Future and Sustainable Energy Systems, Edición June 4 2024, 2025, Página(s) 192-202
Editor: ACM
DOI: 10.1145/3632775.3661956

A Hybrid Graph Network for Complex Activity Detection in Video

Autores: Salman Khan, Izzeddin Teeti, Andrew Bradley, Mohamed Elhoseiny, Fabio Cuzzolin
Publicado en: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Edición 32, 2024, Página(s) 6748-6758
Editor: IEEE
DOI: 10.1109/wacv57701.2024.00662

Value Improved Actor Critic Algorithms

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

Diverse Projection Ensembles for Distributional Reinforcement Learning

Autores: Zanger, Moritz A.; Böhmer, Wendelin; Spaan, Matthijs T. J.
Publicado en: 16th European Workshop on Reinforcement Learning (EWRL 2023), Edición 14 Sep 2023, 2023
Editor: EWRL
DOI: 10.48550/arxiv.2306.07124

A Unified Evaluation Framework for Epistemic Predictions

Autores: S.K. Manchingal, M. Mubashar, K. Wang, F. Cuzzolin
Publicado en: The 28th International Conference on Artificial Intelligence and Statistics, AISTATS 25, Edición 3 May 2025, 2025
Editor: The Proceedings of Machine Learning Research
DOI: 10.48550/arxiv.2501.16912

Bayesian Ensembles for Exploration in Deep Q-Learning

Autores: Pascal Van der Vaart, Neil Yorke-Smith, Matthijs T. J. Spaan
Publicado en: Sixteenth Workshop on Adaptive and Learning Agents (ALA 2024), Edición 6 May 2024, 2024, Página(s) 2528 - 2530
Editor: Adaptive Learning Agents Workshop 2024
DOI: 10.5555/3635637.3663216

Interval Reduced Order Surrogate Modelling Framework for Uncertainty Quantification

Autores: Ghifari A. Faza, Keivan Shariatmadar, Hans Hallez, David Moens
Publicado en: AIAA SCITECH 2024 Forum, Edición 4 Jan 2024, 2024
Editor: American Institute of Aeronautics and Astronautics
DOI: 10.2514/6.2024-0387

A generalisation of the Bellman Equation in Epistemic Reinforcement Learning

Autores: K. Shariatmadar, J. Golub, A. Faza, D. Moens
Publicado en: XAI workshop, Edición May 23 2024, 2024
Editor: Eindhoven Artificial Intelligence Systems Institute
DOI: 10.5281/zenodo.14217032

Epistemic Deep Learning

Autores: Shireen Kudukkil Manchingal, Fabio Cuzzolin
Publicado en: ICML 2022 Workshop on Distribution-Free Uncertainty Quantification, Edición 23 Jul 2022, 2022
Editor: ICML
DOI: 10.48550/arxiv.2206.07609

Diverse Projection Ensembles for Distributional Reinforcement Learning

Autores: Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan
Publicado en: The Twelfth International Conference on Learning Representations (ICLR 2024), Edición 7 May 2024, 2024
Editor: ICLR
DOI: 10.5281/zenodo.14236990

How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning

Autores: M. Weltevrede, M. A. Zanger, M. T. J. Spaan, and W. Böhmer.
Publicado en: The Thirty‑ninth Annual Conference on Neural Information Processing Systems (NeurIPS),, Edición 2 December 2025, 2025
Editor: NeurIPS
DOI: 10.48550/arxiv.2505.16581

Credal Deep Ensembles for Uncertainty Quantification

Autores: Fabio Cuzzolin, Hans Hallez, Shireen Manchingal, David Moens, Keivan Shariatmadar, Kaizheng Wang
Publicado en: Advances in Neural Information Processing Systems 37, Edición 10 December 2024, 2025, Página(s) 79540-79572
Editor: Neural Information Processing Systems Foundation, Inc. (NeurIPS)
DOI: 10.52202/079017-2525

Uncertainty-Aware Autonomous Vehicles: Predicting the Road Ahead

Autores: S.K. Manchingal, A. Amaritei, M. Gohad, M. Sultana, J.F.P. Kooij, F. Cuzzolin, A. Bradley
Publicado en: IEEE International Conference on Robotics & Automation (ICRA 2026), Edición June 1 2026, 2026
Editor: IEEE International Conference on Robotics & Automation (ICRA)
DOI: 10.48550/arxiv.2510.22680

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

Autores: Noah Schutte
Publicado en: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Edición 3-9 Aug 2024, 2024, Página(s) 8504-8505
Editor: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2024/967

Science of AI - Total Uncertainty in AI

Autores: Keivan Shariatmadar
Publicado en: Leuven.AI Workshop, Edición Jun 3 2024, 2024
Editor: KU Leuven
DOI: 10.5281/zenodo.14223938

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

Autores: K. Wang, F. Cuzzolin, K. Shariatmadar, D. Moens, H. Hallez
Publicado en: 3th International Conference on Learning Representations (ICLR 2025), Edición 24 April 2025, 2025, ISBN 9798331320850
Editor: International Conference on Learning Representations (ICLR), POD Curran Associates, Inc.
DOI: 10.48550/arxiv.2405.15047

Universal Value-Function Uncertainties

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

Robust Losses for Decision-Focused Learning

Autores: Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Publicado en: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, Edición 3-9 Aug 2024, 2024, Página(s) 4868-4875
Editor: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2024/538

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

Autores: Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin
Publicado en: 13th International Conference on Learning Representations (ICLR 2025), Edición 24 April 2025, 2025, ISBN 9798331320850
Editor: 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

Autores: Aduen Benjumea, Izzeddin Teeti, Fabio Cuzzolin, Andrew Bradley
Publicado en: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Edición 23 December 2021, 2021
Editor: IEEE
DOI: 10.48550/arxiv.2112.11798

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

Autores: Oren, Yaniv; Spaan, Matthijs T. J.; Böhmer, Wendelin
Publicado en: 13th International Conference on Learning Representations (ICLR 2025), Edición 24 April 2025, 2025, ISBN 9798331320850
Editor: International Conference on Learning Representations (ICLR), POD Curran Associates, Inc.
DOI: 10.48550/arxiv.2210.13455

Autores: M.A. Zanger, P.R. Van der Vaart, W. Boehmer, M.T.J. Spaan
Publicado en: The 14th International Conference on Learning Representations (ICLR 2026), Edición April 23 2026, 2026
Editor: International Conference on Learning Representations (ICLR)
DOI: 10.48550/arxiv.2503.11339

Credal Learning Theory

Autores: Michele Caprio, Fabio Cuzzolin, Eleni Elia, Maryam Sultana
Publicado en: Advances in Neural Information Processing Systems 37, Edición 10 December 2024, 2025, Página(s) 38665-38694
Editor: Neural Information Processing Systems Foundation, Inc. (NeurIPS)
DOI: 10.52202/079017-1221

Epistemic Bellman Operators

Autores: Pascal R. Van der Vaart, Matthijs T. J. Spaan, Neil Yorke-Smith
Publicado en: Proceedings of the AAAI Conference on Artificial Intelligence, Edición 39, 2025, Página(s) 20973-20981, ISSN 2374-3468
Editor: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/aaai.v39i20.35393

Multi-weather city: Adverse weather stacking for autonomous driving

Autores: Valentina Mușat, Ivan Fursa, Paul Newman, Fabio Cuzzolin, Andrew Bradley
Publicado en: 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Edición 11-17 Oct 2021, 2022
Editor: 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

Autores: Yunjia Wang, Kaizheng Wang, Zihao Zhang, Jeroen Boydens, Davy Pissoort, Mathias Verbeke
Publicado en: 2024 IEEE Conference on Artificial Intelligence (CAI), Edición June 25 2024, 2024, Página(s) 985-992
Editor: IEEE
DOI: 10.1109/cai59869.2024.00180

ROAD-R: The Autonomous Driving Dataset with Logical Requirements

Autores: E. Giunchiglia, M. Stoian, S. Khan, F. Cuzzolin and T. Lukasiewicz
Publicado en: IJCAI 2022 - Workshop on Artificial Intelligence for Autonomous Driving (AI4AD 2022), Edición 23 Jul 2022, 2022
Editor: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.48550/arxiv.2210.01597

Epistemic Uncertainty in Artificial Intelligence

Autores: Fabio Cuzzolin, Maryam Sultana
Publicado en: Lecture Notes in Computer Science, Edición 23 Apr 2024, 2024, ISBN 978-3-031-57963-9
Editor: Springer Nature
DOI: 10.1007/978-3-031-57963-9

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

Autores: J. Golub, A. Faza, K. Shariatmadar, D. Moens
Publicado en: MSc dissertation, 2024
Editor: KU Leuven
DOI: 10.5281/zenodo.14223900

Improving Metaheuristic Efficiency for Stochastic Optimization by Sequential Predictive Sampling

Autores: Noah Schutte, Krzysztof Postek, Neil Yorke-Smith
Publicado en: Lecture Notes in Computer Science, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Edición 25 May 2024, 2024, Página(s) 158-175
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-031-60599-4_10

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