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ORCIDWim De Mulder
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2020 – today
- 2023
[j9]Wim De Mulder, Peggy Valcke
, Joke Baeck:
A collaboration between judge and machine to reduce legal uncertainty in disputes concerning ex aequo et bono compensations. Artif. Intell. Law 31(2): 325-333 (2023)- 2022
- [c5]Wim De Mulder:
The Use of Partial Order Relations and Measure Theory in Developing Objective Measures of Explainability. EXTRAAMAS@AAMAS 2022: 173-186 - [c4]Wim De Mulder:
Explainable Black Box Models. IntelliSys (1) 2022: 573-587 - [c3]Henri Arno, Wim De Mulder:
Introduction of Artificial Intelligence in Belgian Court: Failures, Challenges and Opportunities. AI4LEGAL/KGSum@ISWC 2022: 32-40 - 2021
- [c2]Wim De Mulder, Peggy Valcke:
The need for a numeric measure of explainability. IEEE BigData 2021: 2712-2720 - 2020
- [j8]Wim De Mulder, Martin Kuiper:
A foundation for reference models for drug combinations with an application to Loewe's reference model. BMC Bioinform. 21(1): 460 (2020) - [j7]Wim De Mulder, Geert Molenberghs, Geert Verbeke:
An interpretation of radial basis function networks as zero-mean Gaussian process emulators in cluster space. J. Comput. Appl. Math. 363: 249-255 (2020)
2010 – 2019
- 2019
- [j6]Wim De Mulder, Bernhard Rengs, Geert Molenberghs, Thomas Fent, Geert Verbeke:
Extending Gaussian process emulation using cluster analysis and artificial neural networks to fit big training sets. J. Simulation 13(3): 195-208 (2019) - 2015
- [j5]Wim De Mulder, Steven Bethard, Marie-Francine Moens:
A survey on the application of recurrent neural networks to statistical language modeling. Comput. Speech Lang. 30(1): 61-98 (2015) - 2014
- [j4]Wim De Mulder:
Instability and cluster stability variance for real clusterings. Inf. Sci. 260: 51-63 (2014) - 2013
- [j3]Wim De Mulder:
Optimal clustering in the context of overlapping cluster analysis. Inf. Sci. 223: 56-74 (2013) - 2011
- [j2]Wim De Mulder:
Generalized hard cluster analysis. Int. J. Comput. Math. 88(12): 2516-2526 (2011) - 2010
- [j1]Wim De Mulder, Martin Kuiper, René K. Boel:
Clustering of gene expression profiles: creating initialization-independent clusterings by eliminating unstable genes. J. Integr. Bioinform. 7(3) (2010)
2000 – 2009
- 2008
- [c1]Wim De Mulder, Stefan Schliebs, René K. Boel, Martin Kuiper:
Initialization Dependence of Clustering Algorithms. ICONIP (2) 2008: 615-622
Coauthor Index
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