| Top-down induction of clustering trees H Blockeel, L De Raedt, J Ramon arXiv preprint cs/0011032, 2000 | 652 | 2000 |
| Expressivity versus efficiency of graph kernels J Ramon, T Gärtner Proceedings of the first international workshop on mining graphs, trees and …, 2003 | 345 | 2003 |
| Multi instance neural networks J Ramon, L De Raedt Proceedings of the ICML-2000 workshop on attribute-value and relational …, 2000 | 282 | 2000 |
| Machine learning techniques to examine large patient databases G Meyfroidt, F Güiza, J Ramon, M Bruynooghe Best Practice & Research Clinical Anaesthesiology 23 (1), 127-143, 2009 | 171 | 2009 |
| Improving the efficiency of inductive logic programming through the use of query packs H Blockeel, L Dehaspe, B Demoen, G Janssens, J Ramon, ... Journal of Artificial Intelligence Research 16, 135-166, 2002 | 161 | 2002 |
| Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases K Williams, E Bilsland, A Sparkes, W Aubrey, M Young, LN Soldatova, ... Journal of the Royal society Interface 12 (104), 20141289, 2015 | 150 | 2015 |
| Frequent subgraph mining in outerplanar graphs T Horváth, J Ramon, S Wrobel Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 140 | 2006 |
| Hierarchical multi-classification H Blockeel, M Bruynooghe, S Džeroski, J Ramon, J Struyf Workshop Notes of the KDD'02 Workshop on Multi-Relational Data Mining, 21-35, 2002 | 137 | 2002 |
| Speeding up relational reinforcement learning through the use of an incremental first order decision tree learner K Driessens, J Ramon, H Blockeel European Conference on Machine Learning, 97-108, 2001 | 122 | 2001 |
| A polynomial time computable metric between point sets J Ramon, M Bruynooghe Acta Informatica 37 (10), 765-780, 2001 | 119 | 2001 |
| Mining data from intensive care patients J Ramon, D Fierens, F Güiza, G Meyfroidt, H Blockeel, M Bruynooghe, ... Advanced Engineering Informatics 21 (3), 243-256, 2007 | 117 | 2007 |
| Transfer learning in reinforcement learning problems through partial policy recycling J Ramon, K Driessens, T Croonenborghs European conference on machine learning, 699-707, 2007 | 112 | 2007 |
| Relational instance based regression for relational reinforcement learning K Driessens, J Ramon Proceedings of the 20th International Conference on Machine Learning (ICML …, 2003 | 105 | 2003 |
| Monte-Carlo tree search in poker using expected reward distributions G Van den Broeck, K Driessens, J Ramon Advances in Machine Learning: First Asian Conference on Machine Learning …, 2009 | 100 | 2009 |
| Graph kernels and gaussian processes for relational reinforcement learning T Gärtner, K Driessens, J Ramon Inductive Logic Programming: 13th International Conference, ILP 2003, Szeged …, 2003 | 87 | 2003 |
| Logical Bayesian networks and their relation to other probabilistic logical models D Fierens, H Blockeel, M Bruynooghe, J Ramon Inductive Logic Programming: 15th International Conference, ILP 2005, Bonn …, 2005 | 83 | 2005 |
| A framework for defining distances between first-order logic objects J Ramon, M Bruynooghe International Conference on Inductive Logic Programming, 271-280, 1998 | 75 | 1998 |
| Machine learning applications in proteomics research: how the past can boost the future P Kelchtermans, W Bittremieux, K De Grave, S Degroeve, J Ramon, ... Proteomics 14 (4-5), 353-366, 2014 | 68 | 2014 |
| Executing query packs in ILP H Blockeel, L Dehaspe, B Demoen, G Janssens, J Ramon, ... Inductive Logic Programming: 10th International Conference, ILP 2000 London …, 2000 | 68 | 2000 |
| Graph kernels and Gaussian processes for relational reinforcement learning K Driessens, J Ramon, T Gärtner Machine Learning 64 (1), 91-119, 2006 | 67 | 2006 |
