| Artificial intelligence: definition, trends, techniques, and cases JN Kok, EJ Boers, WA Kosters, P Van der Putten, M Poel Artificial intelligence 1 (270-299), 51, 2009 | 382 | 2009 |
| Genetic programming for data classification: Partitioning the search space J Eggermont, JN Kok, WA Kosters Proceedings of the 2004 ACM symposium on Applied computing, 1001-1005, 2004 | 161 | 2004 |
| Data mining approaches to criminal career analysis JS De Bruin, TK Cocx, WA Kosters, JFJ Laros, JN Kok Sixth International Conference on Data Mining (ICDM'06), 171-177, 2006 | 141 | 2006 |
| A caged lanthanide complex as a paramagnetic shift agent for protein NMR M Prudencio, J Rohovec, JA Peters, E Tocheva, MJ Boulanger, ... Chemistry–A European Journal 10 (13), 3252-3260, 2004 | 134 | 2004 |
| Tetris is hard, even to approximate R Breukelaar, ED Demaine, S Hohenberger, HJ Hoogeboom, WA Kosters, ... International Journal of Computational Geometry & Applications 14 (01n02), 41-68, 2004 | 97 | 2004 |
| Determining the diameter of small world networks FW Takes, WA Kosters Proceedings of the 20th ACM international conference on Information and …, 2011 | 94 | 2011 |
| Formal models of appraisal: Theory, specification, and computational model J Broekens, D DeGroot, WA Kosters Cognitive Systems Research 9 (3), 173-197, 2008 | 91 | 2008 |
| Computing the eccentricity distribution of large graphs FW Takes, WA Kosters Algorithms 6 (1), 100-118, 2013 | 86 | 2013 |
| Solving Nonograms by combining relaxations KJ Batenburg, WA Kosters Pattern Recognition 42 (8), 1672-1683, 2009 | 69 | 2009 |
| Fast diameter and radius BFS-based computation in (weakly connected) real-world graphs: With an application to the six degrees of separation games M Borassi, P Crescenzi, M Habib, WA Kosters, A Marino, FW Takes Theoretical Computer Science 586, 59-80, 2015 | 63 | 2015 |
| Complexity analysis of depth first and fp-growth implementations of apriori WA Kosters, W Pijls, V Popova International workshop on machine learning and data mining in pattern …, 2003 | 59 | 2003 |
| Deep model-based reinforcement learning for high-dimensional problems, a survey A Plaat, W Kosters, M Preuss arXiv preprint arXiv:2008.05598, 2020 | 57 | 2020 |
| Mining clusters with association rules WA Kosters, E Marchiori, AAJ Oerlemans International Symposium on Intelligent Data Analysis, 39-50, 1999 | 53 | 1999 |
| Apriori, A Depth First Implementation. WA Kosters, W Pijls FIMI 3, 63, 2003 | 48 | 2003 |
| A discrete tomography approach to Japanese puzzles KJ Batenburg, WA Kosters Proceedings of the 16th Belgium-Netherlands Conference on Artificial …, 2004 | 46 | 2004 |
| Interesting fuzzy association rules in quantitative databases JM de Graaf, WA Kosters, JJW Witteman Principles of Data Mining and Knowledge Discovery: 5th European Conference …, 2001 | 46 | 2001 |
| Applying Monte Carlo techniques to the capacitated vehicle routing problem F Takes, WA Kosters Proceedings of 22th Benelux conference on artificial intelligence (BNAIC 2010), 2010 | 44 | 2010 |
| Affect, anticipation, and adaptation: Affect-controlled selection of anticipatory simulation in artificial adaptive agents J Broekens, WA Kosters, FJ Verbeek Adaptive behavior 15 (4), 397-422, 2007 | 44 | 2007 |
| High-accuracy model-based reinforcement learning, a survey A Plaat, W Kosters, M Preuss Artificial Intelligence Review 56 (9), 9541-9573, 2023 | 40 | 2023 |
| SVision: a deep learning approach to resolve complex structural variants J Lin, S Wang, PA Audano, D Meng, JI Flores, W Kosters, X Yang, P Jia, ... Nature methods 19 (10), 1230-1233, 2022 | 39 | 2022 |
