Logistic model trees N Landwehr, M Hall, E Frank Machine learning 59 (1-2), 161-205, 2005 | 1567 | 2005 |

kFOIL: Learning simple relational kernels N Landwehr, A Passerini, L De Raedt, P Frasconi Aaai 6, 389-394, 2006 | 128 | 2006 |

nFOIL: Integrating naıve bayes and FOIL N Landwehr, K Kersting, L De Raedt Proceedings of the twentieth national conference on artificial intelligence …, 2005 | 107 | 2005 |

Integrating naive bayes and FOIL. N Landwehr, K Kersting, L De Raedt Journal of Machine Learning Research 8 (3), 2007 | 90 | 2007 |

The future agricultural biogas plant in Germany: A vision S Theuerl, C Herrmann, M Heiermann, P Grundmann, N Landwehr, ... Energies 12 (3), 396, 2019 | 71 | 2019 |

A nonergodic ground‐motion model for California with spatially varying coefficients N Landwehr, NM Kuehn, T Scheffer, N Abrahamson Bulletin of the Seismological Society of America 106 (6), 2574-2583, 2016 | 66 | 2016 |

Towards digesting the alphabet-soup of statistical relational learning L De Raedt, B Demoen, D Fierens, B Gutmann, G Janssens, A Kimmig, ... NIPS* 2008 Workshop Probabilistic Programming, Date: 2008/12/13-2008/12/13 …, 2008 | 53 | 2008 |

Active risk estimation C Sawade, N Landwehr, S Bickel, T Scheffer ICML, 2010 | 49 | 2010 |

Stochastic relational processes: Efficient inference and applications I Thon, N Landwehr, L De Raedt Machine Learning 82 (2), 239-272, 2011 | 48 | 2011 |

Relational transformation-based tagging for activity recognition N Landwehr, B Gutmann, I Thon, L De Raedt, M Philipose Fundamenta Informaticae 89 (1), 111-129, 2008 | 45 | 2008 |

Fast learning of relational kernels N Landwehr, A Passerini, L De Raedt, P Frasconi Machine learning 78 (3), 305-342, 2010 | 44 | 2010 |

Modeling interleaved hidden processes N Landwehr Proceedings of the 25th international conference on Machine learning, 520-527, 2008 | 38 | 2008 |

From face to face: the contribution of facial mimicry to cognitive and emotional empathy H Drimalla, N Landwehr, U Hess, I Dziobek Cognition and Emotion, 2019 | 35 | 2019 |

A simple model for sequences of relational state descriptions I Thon, N Landwehr, L De Raedt Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008 | 34 | 2008 |

Boosting relational sequence alignments A Karwath, K Kersting, N Landwehr 2008 Eighth IEEE International Conference on Data Mining, 857-862, 2008 | 28 | 2008 |

Probabilistic seismic hazard analysis in California using nonergodic ground‐motion models NA Abrahamson, NM Kuehn, M Walling, N Landwehr Bulletin of the Seismological Society of America 109 (4), 1235-1249, 2019 | 22 | 2019 |

Active estimation of f-measures C Sawade, N Landwehr, T Scheffer Advances in Neural Information Processing Systems 23, 2083-2091, 2010 | 22 | 2010 |

Learning to identify regular expressions that describe email campaigns P Prasse, C Sawade, N Landwehr, T Scheffer arXiv preprint arXiv:1206.4637, 2012 | 20 | 2012 |

Relational sequence learning K Kersting, L De Raedt, B Gutmann, A Karwath, N Landwehr Probabilistic inductive logic programming, 28-55, 2008 | 20 | 2008 |

Constrained hidden markov models for population-based haplotyping N Landwehr, T Mielikäinen, L Eronen, H Toivonen, H Mannila BMC bioinformatics 8 (S2), S9, 2007 | 20 | 2007 |