Philipp Hennig - Google Scholar Citations

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	All	Since 2015
Citations	2379	2217
h-index	26	24
i10-index	43	40

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20112012201320142015201620172018201920207 14 30 92 144 241 388 487 687 261

Co-authors

Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Stefan SchaalComputer Scientist in Robotics and AIVerified email at google.com
Lukas BallesPhD Student, University of Tuebingen and MPI for Intelligent SystemsVerified email at tuebingen.mpg.de
Mark BangertGerman Cancer Research Center DKFZVerified email at dkfz.de
Michael Tiemann (née Schober)Research scientist, Bosch Center for Artificial IntelligenceVerified email at de.bosch.com
Christian J. SchulerAlumnus, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Thore GraepelResearch Scientist, Google DeepMind, and Professor of Computer Science, UCLVerified email at ucl.ac.uk
Sebastian TrimpeMax Planck Research Group Leader, Max Planck Institute for Intelligent SystemsVerified email at is.mpg.de
Alonso MarcoIntelligent Control Systems, Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Søren HaubergCognitive Systems, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
Michael A OsborneAssociate Professor, University of OxfordVerified email at robots.ox.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
Maren MahsereciAmazon ResearchVerified email at amazon.com
Ralf HerbrichZalandoVerified email at zalando.de
Hans KerstingPhD Student, Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Edgar D. KlenskeBosch Center for Artificial IntelligenceVerified email at de.bosch.com
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Franziska MeierResearch Scientist, Facebook AI ResearchVerified email at fb.com

Philipp Hennig

University of Tübingen & Max Planck Institute for Intelligent Systems

Verified email at tue.mpg.de - Homepage

Probabilistic Numerics Machine Learning


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Entropy search for information-efficient global optimization P Hennig, CJ Schuler Journal of Machine Learning Research 13 (Jun), 1809-1837, 2012	319	2012
Fast bayesian optimization of machine learning hyperparameters on large datasets A Klein, S Falkner, S Bartels, P Hennig, F Hutter arXiv preprint arXiv:1605.07079, 2016	191	2016
Batch bayesian optimization via local penalization J González, Z Dai, P Hennig, N Lawrence Artificial intelligence and statistics, 648-657, 2016	138	2016
The randomized dependence coefficient D Lopez-Paz, P Hennig, B Schölkopf Advances in neural information processing systems, 1-9, 2013	135	2013
Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015	132	2015
Quasi-newton method: A new direction P Hennig, M Kiefel Journal of Machine Learning Research 14 (Mar), 843-865, 2013	85	2013
Probabilistic line searches for stochastic optimization M Mahsereci, P Hennig The Journal of Machine Learning Research 18 (1), 4262-4320, 2017	77	2017
Probabilistic ODE solvers with Runge-Kutta means M Schober, DK Duvenaud, P Hennig Advances in neural information processing systems, 739-747, 2014	72	2014
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	69	2016
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	63	2017
Topic models P Hennig, D Stern, T Graepel, R Herbrich US Patent 8,645,298, 2014	58	2014
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, 2789-2797, 2014	56	2014
Coupling adaptive batch sizes with learning rates L Balles, J Romero, P Hennig arXiv preprint arXiv:1612.05086, 2016	50	2016
Probabilistic interpretation of linear solvers P Hennig SIAM Journal on Optimization 25 (1), 234-260, 2015	47	2015
Incremental local gaussian regression F Meier, P Hennig, S Schaal Advances in Neural Information Processing Systems, 972-980, 2014	46	2014
Active learning of linear embeddings for Gaussian processes R Garnett, MA Osborne, P Hennig arXiv preprint arXiv:1310.6740, 2013	44	2013
Inference of cause and effect with unsupervised inverse regression E Sgouritsa, D Janzing, P Hennig, B Schölkopf Artificial intelligence and statistics, 847-855, 2015	43	2015
Gaussian probabilities and expectation propagation JP Cunningham, P Hennig, S Lacoste-Julien arXiv preprint arXiv:1111.6832, 2011	41	2011
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	40	2015
Probabilistic solutions to differential equations and their application to Riemannian statistics P Hennig, S Hauberg Artificial Intelligence and Statistics, 347-355, 2014	39	2014

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