| Logistic model trees N Landwehr, M Hall, E Frank Machine learning 59 (1), 161-205, 2005 | 1703 | 2005 |
| kFOIL: Learning simple relational kernels N Landwehr, A Passerini, L De Raedt, P Frasconi Aaai 6, 389-394, 2006 | 138 | 2006 |
| nFOIL: Integrating naıve bayes and FOIL N Landwehr, K Kersting, L De Raedt Proceedings of the twentieth national conference on artificial intelligence …, 2005 | 113 | 2005 |
| The future agricultural biogas plant in Germany: A vision S Theuerl, C Herrmann, M Heiermann, P Grundmann, N Landwehr, ... Energies 12 (3), 396, 2019 | 103 | 2019 |
| Integrating naive bayes and FOIL. N Landwehr, K Kersting, L De Raedt Journal of Machine Learning Research 8 (3), 2007 | 97 | 2007 |
| 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 | 87 | 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 | 55 | 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 | 49 | 2019 |
| Stochastic relational processes: Efficient inference and applications I Thon, N Landwehr, L De Raedt Machine Learning 82 (2), 239-272, 2011 | 49 | 2011 |
| Active risk estimation C Sawade, N Landwehr, S Bickel, T Scheffer ICML, 2010 | 49 | 2010 |
| Fast learning of relational kernels N Landwehr, A Passerini, L De Raedt, P Frasconi Machine learning 78 (3), 305-342, 2010 | 46 | 2010 |
| 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 | 46 | 2008 |
| Modeling interleaved hidden processes N Landwehr Proceedings of the 25th international conference on Machine learning, 520-527, 2008 | 39 | 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 | 35 | 2019 |
| A simple model for sequences of relational state descriptions I Thon, N Landwehr, LD 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 |
| Varying-coefficient models for geospatial transfer learning M Bussas, C Sawade, N Kühn, T Scheffer, N Landwehr Machine Learning 106 (9), 1419-1440, 2017 | 24 | 2017 |
| Active estimation of f-measures C Sawade, N Landwehr, T Scheffer Advances in Neural Information Processing Systems 23, 2010 | 24 | 2010 |
| Learning to identify concise regular expressions that describe email campaigns. P Prasse, C Sawade, N Landwehr, T Scheffer J. Mach. Learn. Res. 16 (1), 3687-3720, 2015 | 22 | 2015 |
| Learning to identify regular expressions that describe email campaigns P Prasse, C Sawade, N Landwehr, T Scheffer arXiv preprint arXiv:1206.4637, 2012 | 21 | 2012 |
