| Using internal validity measures to compare clustering algorithms T Van Craenendonck, H Blockeel Benelearn 2015 Poster presentations (online), 1-8, 2015 | 79 | 2015 |
| Constraint-based Clustering Selection T Van Craenendonck, H Blockeel Machine Learning, 2018 | 39 | 2018 |
| Age and sex affect deep learning prediction of cardiometabolic risk factors from retinal images N Gerrits, B Elen, TV Craenendonck, D Triantafyllidou, IN Petropoulos, ... Scientific reports 10 (1), 9432, 2020 | 38 | 2020 |
| Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer’s disease patients S Lemmens, T Van Craenendonck, J Van Eijgen, L De Groef, R Bruffaerts, ... Alzheimer's research & therapy 12 (1), 1-13, 2020 | 32 | 2020 |
| wannesm/dtaidistance v2. 0.0 W Meert, K Hendrickx, T Van Craenendonck Zenodo, 2020 | 25 | 2020 |
| COBRA: A fast and simple method for active clustering with pairwise constraints T Van Craenendonck, S Dumancic, H Blockeel International Joint Conference on Artificial Intelligence (IJCAI) 2017, 2017 | 25 | 2017 |
| COBRASTS: A New Approach to Semi-supervised Clustering of Time Series T Van Craenendonck, W Meert, S Dumančić, H Blockeel Discovery Science: 21st International Conference, DS 2018, Limassol, Cyprus …, 2018 | 19 | 2018 |
| Hyperspectral imaging and the retina: worth the wave? S Lemmens, J Van Eijgen, K Van Keer, J Jacob, S Moylett, L De Groef, ... Translational Vision Science & Technology 9 (9), 9-9, 2020 | 16 | 2020 |
| Cobras: Interactive clustering with pairwise queries T Van Craenendonck, S Dumančić, E Van Wolputte, H Blockeel Advances in Intelligent Data Analysis XVII: 17th International Symposium …, 2018 | 15 | 2018 |
| Systematic comparison of heatmapping techniques in deep learning in the context of diabetic retinopathy lesion detection T Van Craenendonck, B Elen, N Gerrits, P De Boever Translational vision science & technology 9 (2), 64-64, 2020 | 14 | 2020 |
| COBRAS: fast, iterative, active clustering with pairwise constraints T Van Craenendonck, S Dumančić, E Van Wolputte, H Blockeel arXiv preprint arXiv:1803.11060, 2018 | 12 | 2018 |
| Retinal microvascular complexity comparing mono‐and multifractal dimensions in relation to cardiometabolic risk factors in a Middle Eastern population T Van Craenendonck, N Gerrits, B Buelens, IN Petropoulos, A Shuaib, ... Acta Ophthalmologica, 2020 | 9 | 2020 |
| Wannesm/Dtaidistance: v2. 3.5 K Wannesm, A Yurtman, P Robberechts, D Vohl, E Ma, G Verbruggen, ... Zenodo: Genève, Switzerland, 2022 | 7 | 2022 |
| Wannesm/Dtaidistance V1. 1.2 W Meert, T Van Craenendonck Zenodo, 2018 | 3 | 2018 |
| wannesm/dtaidistance: v2. 3.5 A Yurtman, P Robberechts, D Vohl, E Ma, G Verbruggen, M Rossi, ... Zenodo, 2021 | 2 | 2021 |
| Tackling noise in active semi-supervised clustering J Soenen, S Dumančić, T Van Craenendonck, H Blockeel Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020 | 2 | 2020 |
| wannesm/dtaidistance v1. 2.2 T Van Craenendonck, E Ma Zenodo, 2019 | 2 | 2019 |
| System and method for evaluating a performance of explainability methods used with artificial neural networks E Bart, N Gerrits, T Van Craenendonck, P De Boever US Patent App. 17/342,228, 2021 | 1 | 2021 |
| Constraint-based clustering selection T Van Craenendonck, H Blockeel Benelearn 2016 Poster Presentations 2016, 1-3, 2016 | 1 | 2016 |
| Limitations of using constraint set utility in semi-supervised clustering T Van Craenendonck, H Blockeel Proceedings of the 2015 International Workshop on Meta-Learning and …, 2015 | 1 | 2015 |
Hendrik BlockeelDepartment of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
