Niels Landwehr
Niels Landwehr
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Cited by
Cited by
Logistic model trees
N Landwehr, M Hall, E Frank
Machine learning 59, 161-205, 2005
Logistic model trees
N Landwehr, M Hall, E Frank
Machine Learning: ECML 2003: 14th European Conference on Machine Learning …, 2003
The future agricultural biogas plant in Germany: A vision
S Theuerl, C Herrmann, M Heiermann, P Grundmann, N Landwehr, ...
Energies 12 (3), 396, 2019
kFOIL: Learning simple relational kernels
N Landwehr, A Passerini, L De Raedt, P Frasconi
Aaai 6, 389-394, 2006
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
nFOIL: Integrating naıve bayes and FOIL
N Landwehr, K Kersting, L De Raedt
Proceedings of the twentieth national conference on artificial intelligence …, 2005
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
Integrating naive bayes and FOIL.
N Landwehr, K Kersting, L De Raedt
Journal of Machine Learning Research 8 (3), 2007
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
Active risk estimation
C Sawade, N Landwehr, S Bickel, T Scheffer
Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010
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
Stochastic relational processes: Efficient inference and applications
I Thon, N Landwehr, L De Raedt
Machine Learning 82, 239-272, 2011
Fast learning of relational kernels
N Landwehr, A Passerini, L De Raedt, P Frasconi
Machine learning 78, 305-342, 2010
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2016, Riva Del Garda, Italy, September 19-23, 2016, Proceedings, Part II
P Frasconi, N Landwehr, G Manco, J Vreeken
Springer, 2016
Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks
H Tavakoli, P Alirezazadeh, A Hedayatipour, AHB Nasib, N Landwehr
Computers and electronics in agriculture 181, 105935, 2021
Towards the automatic detection of social biomarkers in autism spectrum disorder: Introducing the simulated interaction task (SIT)
H Drimalla, T Scheffer, N Landwehr, I Baskow, S Roepke, B Behnia, ...
NPJ digital medicine 3 (1), 25, 2020
Early detection of stripe rust in winter wheat using deep residual neural networks
M Schirrmann, N Landwehr, A Giebel, A Garz, KH Dammer
Frontiers in plant science 12, 469689, 2021
Optimized deep learning model as a basis for fast UAV mapping of weed species in winter wheat crops
T de Camargo, M Schirrmann, N Landwehr, KH Dammer, M Pflanz
Remote Sensing 13 (9), 1704, 2021
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
Modeling interleaved hidden processes
N Landwehr
Proceedings of the 25th international conference on Machine learning, 520-527, 2008
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