Philipp Hennig

Cited by

	All	Since 2016
Citations	3131	2788
h-index	30	28
i10-index	52	49

940

470

235

705

201120122013201420152016201720182019202020218 15 33 97 151 245 402 488 690 934 14

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Lukas BallesAmazon ResearchVerified email at amazon.com
Stefan SchaalComputer Scientist in Robotics and AIVerified email at google.com
Michael Tiemann (né Schober)Research scientist, Bosch Center for Artificial IntelligenceVerified email at de.bosch.com
Mark BangertGerman Cancer Research Center DKFZVerified email at dkfz.de
Christian J. SchulerAlumnus, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Sebastian TrimpeProfessor, RWTH Aachen UniversityVerified email at dsme.rwth-aachen.de
Alonso MarcoIntelligent Control Systems, Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Thore GraepelResearch Scientist, Google DeepMind, and Professor of Computer Science, UCLVerified email at ucl.ac.uk
Stefan FalknerBosch Center for Artificial IntelligenceVerified email at de.bosch.com
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Aaron KleinAmazon Research BerlinVerified email at cs.uni-freiburg.de
Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Søren HaubergCognitive Systems, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
Maren MahsereciAmazon ResearchVerified email at amazon.com
Edgar D. KlenskeBosch Center for Artificial IntelligenceVerified email at de.bosch.com
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Hans KerstingSIERRA Team, INRIA ParisVerified email at inria.fr
Ralf HerbrichZalandoVerified email at zalando.de
Hans-Peter WieserDKFZ - German Cancer Research CenterVerified email at dkfz-heidelberg.de

Philipp Hennig

University of Tübingen & Max Planck Institute for Intelligent Systems

Verified email at tue.mpg.de - Homepage

Probabilistic Numerics Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Entropy search for information-efficient global optimization P Hennig, CJ Schuler The Journal of Machine Learning Research 13 (1), 1809-1837, 2012	419	2012
Fast bayesian optimization of machine learning hyperparameters on large datasets A Klein, S Falkner, S Bartels, P Hennig, F Hutter Artificial Intelligence and Statistics, 528-536, 2017	277	2017
Batch bayesian optimization via local penalization J González, Z Dai, P Hennig, N Lawrence Artificial intelligence and statistics, 648-657, 2016	190	2016
Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015	166	2015
The randomized dependence coefficient D Lopez-Paz, P Hennig, B Schölkopf Advances in neural information processing systems 26, 1-9, 2013	154	2013
Probabilistic line searches for stochastic optimization M Mahsereci, P Hennig The Journal of Machine Learning Research 18 (1), 4262-4320, 2017	97	2017
Quasi-Newton method: A new direction P Hennig, M Kiefel Journal of Machine Learning Research 14 (Mar), 843-865, 2013	90	2013
Probabilistic ODE solvers with Runge-Kutta means M Schober, DK Duvenaud, P Hennig Advances in neural information processing systems 27, 739-747, 2014	80	2014
Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization A Marco, F Berkenkamp, P Hennig, AP Schoellig, A Krause, S Schaal, ... 2017 IEEE International Conference on Robotics and Automation (ICRA), 1557-1563, 2017	79	2017
Automatic LQR tuning based on Gaussian process global optimization A Marco, P Hennig, J Bohg, S Schaal, S Trimpe 2016 IEEE international conference on robotics and automation (ICRA), 270-277, 2016	77	2016
Sampling for inference in probabilistic models with fast Bayesian quadrature T Gunter, MA Osborne, R Garnett, P Hennig, SJ Roberts Advances in neural information processing systems 27, 2789-2797, 2014	74	2014
Coupling adaptive batch sizes with learning rates L Balles, J Romero, P Hennig arXiv preprint arXiv:1612.05086, 2016	65	2016
Active learning of linear embeddings for Gaussian processes R Garnett, MA Osborne, P Hennig arXiv preprint arXiv:1310.6740, 2013	65	2013
Gaussian processes and kernel methods: A review on connections and equivalences M Kanagawa, P Hennig, D Sejdinovic, BK Sriperumbudur arXiv preprint arXiv:1807.02582, 2018	64	2018
Topic models P Hennig, D Stern, T Graepel, R Herbrich US Patent 8,645,298, 2014	64	2014
Incremental local gaussian regression F Meier, P Hennig, S Schaal Advances in Neural Information Processing Systems 27, 972-980, 2014	57	2014
Probabilistic interpretation of linear solvers P Hennig SIAM Journal on Optimization 25 (1), 234-260, 2015	55	2015
Inference of cause and effect with unsupervised inverse regression E Sgouritsa, D Janzing, P Hennig, B Schölkopf Artificial intelligence and statistics, 847-855, 2015	53	2015
Gaussian process-based predictive control for periodic error correction ED Klenske, MN Zeilinger, B Schölkopf, P Hennig IEEE Transactions on Control Systems Technology 24 (1), 110-121, 2015	48	2015
Kernel topic models P Hennig, D Stern, R Herbrich, T Graepel Artificial Intelligence and Statistics, 511-519, 2012	48	2012

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