Gilles Vandewiele
Gilles Vandewiele
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Zitiert von
Zitiert von
Tslearn, a machine learning toolkit for time series data.
R Tavenard, J Faouzi, G Vandewiele, F Divo, G Androz, C Holtz, M Payne, ...
J. Mach. Learn. Res. 21 (118), 1-6, 2020
Overly optimistic prediction results on imbalanced data: a case study of flaws and benefits when applying over-sampling
G Vandewiele, I Dehaene, G Kovács, L Sterckx, O Janssens, F Ongenae, ...
Artificial Intelligence in Medicine 111, 101987, 2021
A genetic algorithm for interpretable model extraction from decision tree ensembles
G Vandewiele, K Lannoye, O Janssens, F Ongenae, F De Turck, ...
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 104-115, 2017
Real-time Data Dissemination and Analytics Platform for Challenging IoT Environments
G Daneels, E Municio, K Spaey, G Vandewiele, A Dejonghe, F Ongenae, ...
GIIS 2017, 2017
CSV2KG: transforming tabular data into semantic knowledge
B Steenwinckel, G Vandewiele, F De Turck, F Ongenae
SemTab, ISWC Challenge, 33-40, 2019
Modeling the prediction of the session rating of perceived exertion in soccer: Unraveling the puzzle of predictive indicators
Y Geurkink, G Vandewiele, M Lievens, F De Turck, F Ongenae, ...
International journal of sports physiology and performance 14 (6), 841-846, 2019
Predicting train occupancies based on query logs and external data sources
G Vandewiele, P Colpaert, O Janssens, J Van Herwegen, R Verborgh, ...
Proceedings of the 26th International Conference on World Wide Web Companion …, 2017
A decision support system to follow up and diagnose primary headache patients using semantically enriched data
G Vandewiele, F De Backere, K Lannoye, M Vanden Berghe, O Janssens, ...
BMC medical informatics and decision making 18 (1), 1-15, 2018
MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph
G Vandewiele, B Steenwinckel, FD Turck, F Ongenae
BMC Medical Informatics and Decision Making 20 (4), 1-15, 2020
Facilitating the analysis of COVID-19 literature through a knowledge graph
B Steenwinckel, G Vandewiele, I Rausch, P Heyvaert, R Taelman, ...
International Semantic Web Conference, 344-357, 2020
Data mining in the development of mobile health apps: Assessing in-app navigation through Markov chain analysis
J Stragier, G Vandewiele, P Coppens, F Ongenae, W Van den Broeck, ...
Journal of medical Internet research 21 (6), e11934, 2019
Walk extraction strategies for node embeddings with rdf2vec in knowledge graphs
B Steenwinckel, G Vandewiele, P Bonte, M Weyns, H Paulheim, ...
International Conference on Database and Expert Systems Applications, 70-80, 2021
pyRDF2Vec: A Python Implementation and Extension of RDF2Vec
G Vandewiele, B Steenwinckel, T Agozzino, F Ongenae
arXiv preprint arXiv:2205.02283, 2022
GENDIS: Genetic discovery of shapelets
G Vandewiele, F Ongenae, F De Turck
Sensors 21 (4), 1059, 2021
Training progression in recreational cyclists: no linear dose-response relationship with training load
K Vermeire, G Vandewiele, K Caen, M Lievens, JG Bourgois, J Boone
Journal of Strength and Conditioning Research, 2019
INK: knowledge graph embeddings for node classification
B Steenwinckel, G Vandewiele, M Weyns, T Agozzino, FD Turck, ...
Data Mining and Knowledge Discovery 36 (2), 620-667, 2022
Clinical information extraction for preterm birth risk prediction
L Sterckx, G Vandewiele, I Dehaene, O Janssens, F Ongenae, ...
Journal of Biomedical Informatics 110, 103544, 2020
Enhancing white-box machine learning processes by incorporating semantic background knowledge
G Vandewiele
European Semantic Web Conference, 267-278, 2017
Time-to-birth prediction models and the influence of expert opinions
G Vandewiele, I Dehaene, O Janssens, F Ongenae, FD Backere, ...
Conference on artificial intelligence in medicine in Europe, 286-291, 2019
R-GCN: The R Could Stand for Random
V Degraeve, G Vandewiele, F Ongenae, S Van Hoecke
arXiv preprint arXiv:2203.02424, 2022
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