David Moens - RankMe

19 papers A* 3Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Review of Uncertainty Representation and Quantification in Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez
2026	A*	`conf`	Credal Ensemble Distillation for Uncertainty Quantification. AAAI Kaizheng Wang, Fabio Cuzzolin, David Moens, Hans Hallez
2026	J	`jnl`	Direct Interval Propagation Methods using Neural-Network Surrogates for Uncertainty Quantification in Physical Systems Surrogate Model. CoRR Ghifari Adam Faza, Jolan Wauters, Fabio Cuzzolin, Hans Hallez, David Moens
2026	J	`jnl`	Learning Credal Ensembles via Distributionally Robust Optimization. CoRR Kaizheng Wang, Ghifari Adam Faza, Fabio Cuzzolin, Siu Lun Chau, David Moens, Hans Hallez
2026	J	`jnl`	Set-based v.s. Distribution-based Representations of Epistemic Uncertainty: A Comparative Study. CoRR Kaizheng Wang, Yunjia Wang, Fabio Cuzzolin, David Moens, Hans Hallez, Siu Lun Chau
2025	J	`jnl`	CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks. Neural Networks Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
2025	J	`jnl`	Credal Ensemble Distillation for Uncertainty Quantification. CoRR Kaizheng Wang, Fabio Cuzzolin, David Moens, Hans Hallez
2025	A*	`conf`	Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification. ICLR Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez
2025	J	`jnl`	Generalized Decision Focused Learning under Imprecise Uncertainty-Theoretical Study. CoRR Keivan Shariatmadar, Neil Yorke-Smith, Ahmad Osman, Fabio Cuzzolin, Hans Hallez, David Moens
2025	J	`jnl`	Most likely heteroscedastic Gaussian process via kernel smoothing. Knowl. Based Syst. Ghifari Adam Faza, Nasrulloh R. B. S. Loka, Keivan Shariatmadar, Hans Hallez, David Moens
2024	J	`jnl`	CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks. CoRR Kaizheng Wang, Keivan Shariatmadar, Shireen Kudukkil Manchingal, Fabio Cuzzolin, David Moens, Hans Hallez
2024	A*	`conf`	Credal Deep Ensembles for Uncertainty Quantification. NeurIPS Kaizheng Wang, Fabio Cuzzolin, Shireen Kudukkil Manchingal, Keivan Shariatmadar, David Moens, Hans Hallez
2024	J	`jnl`	Credal Wrapper of Model Averaging for Uncertainty Estimation on Out-Of-Distribution Detection. CoRR Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez
2024	J	`jnl`	Reliability evaluation of a multi-state system with dependent components and imprecise parameters: A structural reliability treatment. Reliab. Eng. Syst. Saf. Lechang Yang, Xinyao Zhang, Zitong Lu, Yuqiang Fu, David Moens, Michael Beer
2022	J	`jnl`	An introduction to optimization under uncertainty - A short survey. CoRR Keivan Shariatmadar, Kaizheng Wang, Calvin R. Hubbard, Hans Hallez, David Moens
2021	J	`jnl`	Computationally Efficient Optimization Method to Quantify the Required Surgical Accuracy for a Ligament Balanced TKA. IEEE Trans. Biomed. Eng. Laura Bartsoen, Matthias G. R. Faes, Mariska Wesseling, Roel Wirix-Speetjens, David Moens, Ilse Jonkers, Jos Vander Sloten
2019	—	`conf`	A fast inverse approach for the quantification of set-theoretical uncertainty. SSCI Lars Bogaerts, Matthias G. R. Faes, David Moens
2019	J	`jnl`	Hybrid spatial uncertainty analysis for the estimation of imprecise failure probabilities in Laser Sintered PA-12 parts. Comput. Math. Appl. Matthias G. R. Faes, Ghosh Dastidar Sabyasachi, David Moens
2017	—	`conf`	Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure. SSCI Matteo Broggi, Matthias G. R. Faes, Edoardo Patelli, Yves Govers, David Moens, Michael Beer