Ghent University Academic Bibliography

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Proceedings of the Fourteenth International Symposium on Imprecise Probabilities : Theories and Applications

Sébastien Destercke, Alexander Erreygers (UGent) , Max Nendel, Frank Riedel and Matthias C. M. Troffaes

(2025) PROCEEDINGS OF MACHINE LEARNING RESEARCH. 290.
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ABCFair : an adaptable benchmark approach for comparing fairness methods

Marybeth Defrance (UGent) , Maarten Buyl (UGent) and Tijl De Bie (UGent)

(2025) PROCEEDINGS OF MACHINE LEARNING RESEARCH. 294. p.383-388
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Robustness quantification : a new method for assessing the reliability of the predictions of a classifier

Adrian Detavernier (UGent) and Jasper De Bock (UGent)

(2025) INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITIES: THEORIES AND APPLICATIONS. In Proceedings of machine learning research 290. p.126-136
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A convenient characterisation of convergent upper transition operators

Jasper De Bock (UGent) , Alexander Erreygers (UGent) and Floris Persiau (UGent)

(2025) INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITIES: THEORIES AND APPLICATIONS. In Proceedings of Machine Learning Research 290. p.115-125
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Privacy-preserving group fairness in cross-device federated learning

Sikha Pentyala, Nicola Neophytou, Anderson Nascimento, Martine De Cock (UGent) and Golnoosh Farnadi

(2025) Proceedings of the algorithmic fairness through the lens of metrics and evaluation. In Proceedings of Machine Learning Research 279. p.173-198
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Conditioning and AGM-like belief change in the Desirability-Indifference framework

Kathelijne Coussement (UGent) , Gert de Cooman (UGent) and Keano De Vos (UGent)

(2025) INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITIES: THEORIES AND APPLICATIONS. In Proceedings of machine learning research 290. p.82-92
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Loop closure with a low power millimeter wave radar sensor using an autoencoder

Pieter Meiresone (UGent) , David Van Hamme (UGent) and Wilfried Philips (UGent)

(2024) NORTHERN LIGHTS DEEP LEARNING CONFERENCE, VOL 233. In Proceedings of Machine Learning Research 233. p.153-157
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Conformal predictive systems under covariate shift

Jef Jonkers (UGent) , Glenn Van Wallendael (UGent) , Luc Duchateau (UGent) and Sofie Van Hoecke (UGent)

(2024) 13TH SYMPOSIUM ON CONFORMAL AND PROBABILISTIC PREDICTION WITH APPLICATIONS. In Proceedings of Machine Learning Research 230. p.406-423
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Accelerating Hopfield network dynamics : beyond synchronous updates and forward Euler

Cédric Goemaere (UGent) , Johannes Deleu (UGent) and Thomas Demeester (UGent)

(2024) 1ST ECAI WORKSHOP ON MACHINE LEARNING MEETS DIFFERENTIAL EQUATIONS : FROM THEORY TO APPLICATIONS. In Proceedings of Machine Learning Research 255.
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Is epistemic uncertainty faithfully represented by evidential deep learning methods?

Mira Kristin Jürgens (UGent) , Nis Meinert, Viktor Bengs, Eyke Hüllermeier and Willem Waegeman (UGent)

(2024) 41st International Conference on Machine Learning (ICML), Proceedings. In Proceedings of Machine Learning Research 235. p.22624-22642

Academic Bibliography

Proceedings of the Fourteenth International Symposium on Imprecise Probabilities : Theories and Applications

ABCFair : an adaptable benchmark approach for comparing fairness methods

Robustness quantification : a new method for assessing the reliability of the predictions of a classifier

A convenient characterisation of convergent upper transition operators

Privacy-preserving group fairness in cross-device federated learning

Conditioning and AGM-like belief change in the Desirability-Indifference framework

Loop closure with a low power millimeter wave radar sensor using an autoencoder

Conformal predictive systems under covariate shift

Accelerating Hopfield network dynamics : beyond synchronous updates and forward Euler

Is epistemic uncertainty faithfully represented by evidential deep learning methods?

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