Academic Bibliography

Search 200 years of publications by Ghent University researchers.

dr. Thomas Mortier

Faculty of Bioscience Engineering > Department of Environment

ORCID iD: 0000-0001-9650-9263

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- Journal Article
- A1
- open access
Uncertainty-aware single-cell annotation with a hierarchical reject option

Lauren Theunissen (UGent) , Thomas Mortier (UGent) , Yvan Saeys (UGent) and Willem Waegeman (UGent)

(2024) BIOINFORMATICS. 40(3).
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- Journal Article
- A1
- open access
A framework for tracing timber following the Ukraine invasion

Thomas Mortier (UGent) , Jakub Truszkowski, Marigold Norman, Markus Boner, Bogdan Buliga, Caspar Chater, Henry Jennings, Jade Saunders, Rosie Sibley, Alexandre Antonelli, et al.

(2024) NATURE PLANTS. 10(3). p.390-401
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- PhD Thesis
Efﬁcient algorithms for set-valued prediction in classiﬁcation

Thomas Mortier (UGent)

(2023)
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- Conference Paper
- P1
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On the calibration of probabilistic classifier sets

Thomas Mortier (UGent) , Viktor Bengs, Eyke Hüllermeier, Stijn Luca (UGent) and Willem Waegeman (UGent)

(2023) INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 206. In Proceedings of Machine Learning Research 206. p.8857-8870
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- Conference Paper
- C1
- open access
Set-valued prediction in hierarchical classification with constrained representation complexity

Thomas Mortier (UGent) , Eyke Hüllermeier, Krzysztof Dembczynski and Willem Waegeman (UGent)

(2022) Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence. In Proceedings of Machine Learning Research 180. p.1392-1401
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- Journal Article
- A1
- open access
Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques : a large-scale benchmarking study

Thomas Mortier (UGent) , Anneleen Wieme (UGent) , Peter Vandamme (UGent) and Willem Waegeman (UGent)

(2021) COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL. 19. p.6157-6168
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Efficient set-valued prediction in multi-class classification

Thomas Mortier (UGent) , Marek Wydmuch, Krzysztof Dembczynski, Eyke Huellermeier and Willem Waegeman (UGent)

(2021) DATA MINING AND KNOWLEDGE DISCOVERY. 35(4). p.1435-1469
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- Conference Paper
- C3
- open access
Set-Valued Prediction in Multi-Class Classification

Thomas Mortier (UGent) , Marek Wydmuch, Krzysztof Dembczyński, Eyke Hüllermeier and Willem Waegeman (UGent)

(2019) BNAIC/BENELEARN 2019 : proceedings of the reference AI & ML conference for Belgium, Netherlands & Luxemburg. In CEUR Workshop Proceedings 2491.
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A protocol for automated timber species identification using metabolome profiling

Victor Deklerck, Thomas Mortier (UGent) , Nathalie Goeders, RB Cody, Willem Waegeman (UGent) , E Espinoza, Joris Van Acker (UGent) , Jan Van den Bulcke (UGent) and H Beeckman

(2019) WOOD SCIENCE AND TECHNOLOGY. 53(4). p.953-965
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Deep F-measure maximization in multi-label classification : a comparative study

Stijn Decubber (UGent) , Thomas Mortier (UGent) , Krzysztof Dembczyński and Willem Waegeman (UGent)

(2018) Machine learning and knowledge discovery in databases : European conference, ECML PKDD 2018 : proceedings, part I. In Lecture Notes in Computer Science 11051. p.290-305