Daniel Bethell

According to our database, Daniel Bethell authored at least 9 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Learning to Navigate Under Imperfect Perception: Conformalised Segmentation for Safe Reinforcement Learning.

Daniel Bethell, Simos Gerasimou, Radu Calinescu, Calum Imrie

Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing, 2026

Multi-Partner Project: Enhancing Resilience, Efficiency, and Trustworthiness of Edge AI in Safety-Critical Systems (GuardAI).

Antonis D. Savva, Mehmet Demirel, Yeshwanth Kumar Adimoolam, Rafaella Elia, Alexandros Gkillas, Christos Anagnostopoulos, Erion-Vasilis M. Pikoulis, Amalia Damianou, Charmaine Barker, Daniel Bethell, Ahmed Salah Tawfik Ibrahim, Filippo Cugini, Francesco Paolucci, Kyriakos Vlachos, Simos Gerasimou, Antonios Lalas, Konstantinos Votis, Aris S. Lalos, Christos Kyrkou, Theocharis Theocharides

Proceedings of the Design, Automation & Test in Europe Conference, 2026

2025

Safe But Not Sorry: Reducing Over-Conservatism in Safety Critics via Uncertainty-Aware Modulation.

Daniel Bethell, Simos Gerasimou, Radu Calinescu, Calum Imrie

CoRR, October, 2025

Guided Uncertainty Learning Using a Post-Hoc Evidential Meta-Model.

Charmaine Barker, Daniel Bethell, Simos Gerasimou

CoRR, September, 2025

Quantifying Adversarial Uncertainty in Evidential Deep Learning using Conflict Resolution.

Charmaine Barker, Daniel Bethell, Simos Gerasimou

CoRR, June, 2025

Learning Fairer Representations with FairVIC.

Charmaine Barker, Daniel Bethell, Dimitar Kazakov

Proceedings of TRUST-AI 2025, 2025

Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding.

Daniel Bethell, Simos Gerasimou, Radu Calinescu, Calum Imrie

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

Enhancing Fairness in Neural Networks Using FairVIC.

Charmaine Barker, Daniel Bethell, Dimitar Kazakov

CoRR, 2024

Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction.

Daniel Bethell, Simos Gerasimou, Radu Calinescu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024