Kristian Kersting

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Luc De Raedtprofessor, KU LeuvenDirección de correo verificada de cs.kuleuven.be
Sriraam NatarajanUniversity of Texas at DallasDirección de correo verificada de utdallas.edu
Christian BauckhageProf. of Computer Science, University of Bonn, Fraunhofer IAISDirección de correo verificada de bit.uni-bonn.de
Mirwaes WahabzadaBASF Digital Farming GmbHDirección de correo verificada de basf.com
Tushar KhotAllen Institute for AI; University of Wisconsin-MadisonDirección de correo verificada de cs.wisc.edu
Marion NeumannWashington University in St. LouisDirección de correo verificada de wustl.edu
Christian ThurauAmbidexterDirección de correo verificada de ambidexter.gmbh
Fabian Hadijigoedle.io GmbHDirección de correo verificada de goedle.io
Wolfram BurgardProfessor of Computer Science, University of FreiburgDirección de correo verificada de informatik.uni-freiburg.de
Alejandro MolinaTU DarmstadtDirección de correo verificada de cs.tu-darmstadt.de
Jude ShavlikProfessor of Computer Science and of Biostatistics & Medical Informatics, University of WisconsinDirección de correo verificada de cs.wisc.edu
Christian PlagemannGoogle ResearchDirección de correo verificada de google.com
Babak AhmadiFraunhofer IAISDirección de correo verificada de iais.fraunhofer.de
Anne-Katrin MahleinInstitute of Sugar Beet Reserach, GöttingenDirección de correo verificada de ifz-goettingen.de
Martin MladenovGoogle ResearchDirección de correo verificada de google.com
Zhao XuNEC Labs EuropeDirección de correo verificada de acm.org
Petra MutzelProfessorin für Informatik, Universität BonnDirección de correo verificada de cs.uni-bonn.de
Roman GarnettWashington University in St. LouisDirección de correo verificada de wustl.edu
Antonio VergariPostDoc, University of California, Los AngelesDirección de correo verificada de cs.ucla.edu
Christopher MorrisPostdoc, Polytechnique MontréalDirección de correo verificada de christophermorris.info

Kristian Kersting

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

Dirección de correo verificada de cs.tu-darmstadt.de - Página principal

Artificial Intelligence Statistical Relational Learning Probabilistic Programming Tractable Models Plant Phenotyping


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1714	2007
Probabilistic Inductive Logic Programming L De Raedt, K Kersting Probabilistic Inductive Logic Programming - Theory and Applications, 1-27, 2008	462	2008
Bayesian logic programs K Kersting, L De Raedt arXiv preprint cs/0111058, 2001	311	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	301	2007
Lifted Probabilistic Inference with Counting Formulas. B Milch, LS Zettlemoyer, K Kersting, M Haimes, LP Kaelbling Aaai 8, 1062-1068, 2008	223	2008
Probabilistic logic learning L De Raedt, K Kersting ACM SIGKDD Explorations Newsletter 5 (1), 31-48, 2003	213	2003
Bayesian Logic Programming: Theory and Tool K Kersting, L De Raedt Introduction to Statistical Relational Learning, 291, 2007	193	2007
Counting belief propagation K Kersting, B Ahmadi, S Natarajan arXiv preprint arXiv:1205.2637, 2012	178	2012
Towards combining inductive logic programming with Bayesian networks K Kersting, L De Raedt International Conference on Inductive Logic Programming, 118-131, 2001	178	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	168	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	147	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
Probabilistic Inductive Logic Programming-Theory and Applications LD Raedt, P Frasconi, K Kersting, S Muggleton Lecture Notes in Computer Science 4911, 2008	134*	2008
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	121	2012
Logical hidden markov models K Kersting, L De Raedt, T Raiko Journal of Artificial Intelligence Research 25, 425-456, 2006	119	2006
Propagation kernels: efficient graph kernels from propagated information M Neumann, R Garnett, C Bauckhage, K Kersting Machine Learning 102 (2), 209-245, 2016	109	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), 28, 2015	108	2015
Lifted Probabilistic Inference. K Kersting ECAI, 33-38, 2012	106	2012
nFOIL: Integrating naıve bayes and FOIL N Landwehr, K Kersting, L De Raedt Proceedings of the twentieth national conference on artificial intelligence …, 2005	106	2005

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