Top-down induction of first-order logical decision trees H Blockeel, L De Raedt Artificial intelligence 101 (1-2), 285-297, 1998 | 922 | 1998 |

Top-down induction of clustering trees H Blockeel, L De Raedt, J Ramon arXiv preprint cs/0011032, 2000 | 537 | 2000 |

Expressivity versus efficiency of graph kernels J Ramon, T Gärtner Proceedings of the first international workshop on mining graphs, trees and …, 2003 | 275 | 2003 |

Multi instance neural networks J Ramon, L De Raedt Proceedings of the ICML-2000 workshop on attribute-value and relational …, 2000 | 189 | 2000 |

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 | 153 | 2002 |

Frequent subgraph mining in outerplanar graphs T Horváth, J Ramon, S Wrobel Data Mining and Knowledge Discovery 21 (3), 472-508, 2010 | 128 | 2010 |

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 | 125 | 2009 |

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 | 115 | 2002 |

A polynomial time computable metric between point sets J Ramon, M Bruynooghe Acta Informatica 37 (10), 765-780, 2001 | 112 | 2001 |

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 | 108 | 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 | 98 | 2007 |

Exponential and geometric kernels for graphs T Gartner NIPS^* 02 Workshop on Unreal Data: Principles of Modeling Nonvectorial Data, 2002 | 95 | 2002 |

Relational instance based regression for relational reinforcement learning K Driessens, J Ramon Proceedings of the 20th International Conference on Machine Learning (ICML …, 2003 | 93 | 2003 |

Relational reinforcement learning K Driessens AI Communications 18 (1), 71-73, 2005 | 84* | 2005 |

Transfer learning in reinforcement learning problems through partial policy recycling J Ramon, K Driessens, T Croonenborghs European Conference on Machine Learning, 699-707, 2007 | 82 | 2007 |

Graph kernels and gaussian processes for relational reinforcement learning T Gärtner, K Driessens, J Ramon International Conference on Inductive Logic Programming, 146-163, 2003 | 82 | 2003 |

Logical Bayesian networks and their relation to other probabilistic logical models D Fierens, H Blockeel, M Bruynooghe, J Ramon International Conference on Inductive Logic Programming, 121-135, 2005 | 80 | 2005 |

Monte-Carlo tree search in poker using expected reward distributions G Van den Broeck, K Driessens, J Ramon Asian Conference on Machine Learning, 367-381, 2009 | 76 | 2009 |

A framework for defining distances between first-order logic objects J Ramon, M Bruynooghe International Conference on Inductive Logic Programming, 271-280, 1998 | 70 | 1998 |

Executing query packs in ILP H Blockeel, L Dehaspe, B Demoen, G Janssens, J Ramon, ... International Conference on Inductive Logic Programming, 60-77, 2000 | 68 | 2000 |