Kristian Kersting

Cited by

	All	Since 2016
Citations	10905	5231
h-index	51	32
i10-index	173	124

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Co-authors

Luc De Raedtprofessor, KU LeuvenVerified email at cs.kuleuven.be
Sriraam NatarajanUniversity of Texas at DallasVerified email at utdallas.edu
Christian BauckhageProf. of Computer Science, University of Bonn, Fraunhofer IAISVerified email at bit.uni-bonn.de
Mirwaes WahabzadaBASF Digital Farming GmbHVerified email at basf.com
Tushar KhotAllen Institute for AI; University of Wisconsin-MadisonVerified email at cs.wisc.edu
Marion NeumannWashington University in St. LouisVerified email at wustl.edu
Fabian Hadijigoedle.io GmbHVerified email at goedle.io
Wolfram BurgardProfessor of Computer Science, University of FreiburgVerified email at informatik.uni-freiburg.de
Alejandro MolinaTU DarmstadtVerified email at cs.tu-darmstadt.de
Christian ThurauAmbidexterVerified email at ambidexter.gmbh
Jude ShavlikProfessor of Computer Science and of Biostatistics & Medical Informatics, University of WisconsinVerified email at cs.wisc.edu
Christian PlagemannGoogle ResearchVerified email at google.com
Babak AhmadiFraunhofer IAISVerified email at iais.fraunhofer.de
Anne-Katrin MahleinInstitute of Sugar Beet Reserach, GöttingenVerified email at ifz-goettingen.de
Martin MladenovGoogle ResearchVerified email at google.com
Zhao XuNEC Labs EuropeVerified email at acm.org
Petra MutzelProfessorin für Informatik, Universität BonnVerified email at cs.uni-bonn.de
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Antonio VergariPostDoc, University of California, Los AngelesVerified email at cs.ucla.edu
Saket JoshiApplied Scientist, AmazonVerified email at amazon.com

Kristian Kersting

Professor of Artificial Intelligence and Machine Learning, hessian.ai, TU Darmstadt

Verified email at cs.tu-darmstadt.de - Homepage

Artificial Intelligence Statistical Relational Learning Probabilistic Programming Tractable Models Plant Phenotyping


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Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1717	2007
Probabilistic Inductive Logic Programming L De Raedt, K Kersting Probabilistic Inductive Logic Programming - Theory and Applications, 1-27, 2008	470	2008
Bayesian logic programs K Kersting, L De Raedt arXiv preprint cs/0111058, 2001	313	2001
Most likely heteroscedastic Gaussian process regression K Kersting, C Plagemann, P Pfaff, W Burgard Proceedings of the 24th international conference on Machine learning, 393-400, 2007	298	2007
Lifted Probabilistic Inference with Counting Formulas. B Milch, LS Zettlemoyer, K Kersting, M Haimes, LP Kaelbling Aaai 8, 1062-1068, 2008	226	2008
Probabilistic logic learning L De Raedt, K Kersting ACM SIGKDD Explorations Newsletter 5 (1), 31-48, 2003	215	2003
Bayesian Logic Programming: Theory and Tool K Kersting, L De Raedt Introduction to Statistical Relational Learning, 291, 2007	194	2007
Counting belief propagation K Kersting, B Ahmadi, S Natarajan arXiv preprint arXiv:1205.2637, 2012	180	2012
Towards combining inductive logic programming with Bayesian networks K Kersting, L De Raedt International Conference on Inductive Logic Programming, 118-131, 2001	180	2001
Statistical relational artificial intelligence: Logic, probability, and computation LD Raedt, K Kersting, S Natarajan, D Poole Synthesis Lectures on Artificial Intelligence and Machine Learning 10 (2), 1-189, 2016	166	2016
Predicting player churn in the wild F Hadiji, R Sifa, A Drachen, C Thurau, K Kersting, C Bauckhage 2014 IEEE Conference on Computational Intelligence and Games, 1-8, 2014	146	2014
Bellman goes relational K Kersting, MV Otterlo, L De Raedt Proceedings of the twenty-first international conference on Machine learning, 59, 2004	146	2004
Gradient-based boosting for statistical relational learning: The relational dependency network case S Natarajan, T Khot, K Kersting, B Gutmann, J Shavlik Machine Learning 86 (1), 25-56, 2012	141	2012
Benchmark data sets for graph kernels, 2016 K Kersting, NM Kriege, C Morris, P Mutzel, M Neumann URL http://graphkernels. cs. tu-dortmund. de 795, 2016	128	2016
Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis C Römer, M Wahabzada, A Ballvora, F Pinto, M Rossini, C Panigada, ... Functional Plant Biology 39 (11), 878-890, 2012	122	2012
Logical hidden markov models K Kersting, L De Raedt, T Raiko Journal of Artificial Intelligence Research 25, 425-456, 2006	121	2006
Propagation kernels: efficient graph kernels from propagated information M Neumann, R Garnett, C Bauckhage, K Kersting Machine Learning 102 (2), 209-245, 2016	110	2016
Hyperspectral phenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions M Kuska, M Wahabzada, M Leucker, HW Dehne, K Kersting, EC Oerke, ... Plant methods 11 (1), 1-15, 2015	108	2015
Lifted Probabilistic Inference. K Kersting ECAI, 33-38, 2012	107	2012
nFOIL: Integrating naıve bayes and FOIL N Landwehr, K Kersting, L De Raedt Proceedings of the twentieth national conference on artificial intelligence …, 2005	104	2005

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