Publications

DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation


Research Groups

Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group


Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

Career

Award


Probabilistic Numerics Perceiving Systems Conference Paper Coupling Adaptive Batch Sizes with Learning Rates Balles, L., Romero, J., Hennig, P. In Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), ID 141, (Editors: Gal Elidan, Kristian Kersting, and Alexander T. Ihler), August 2017 (Published) Code URL BibTeX

Autonomous Motion Probabilistic Numerics Intelligent Control Systems Conference Paper Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization Marco, A., Berkenkamp, F., Hennig, P., Schoellig, A. P., Krause, A., Schaal, S., Trimpe, S. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 1557-1563, IEEE, Piscataway, NJ, USA, May 2017 (Published) PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Approximate dual control maintaining the value of information with an application to building control Klenske, E. D., Hennig, P., Schölkopf, B., Zeilinger, M. N. In European Control Conference (ECC), 800-806, June 2016 PDF DOI BibTeX

Autonomous Motion Probabilistic Numerics Intelligent Control Systems Conference Paper Automatic LQR Tuning Based on Gaussian Process Global Optimization Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (Published) Video - Automatic LQR Tuning Based on Gaussian Process Global Optimization - ICRA 2016 Video - Automatic Controller Tuning on a Two-legged Robot PDF DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper A Random Riemannian Metric for Probabilistic Shortest-Path Tractography Hauberg, S., Schober, M., Liptrot, M., Hennig, P., Feragen, A. In 18th International Conference on Medical Image Computing and Computer Assisted Intervention, 9349:597-604, Lecture Notes in Computer Science, MICCAI, 2015 (Published) PDF DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Inference of Cause and Effect with Unsupervised Inverse Regression Sgouritsa, E., Janzing, D., Hennig, P., Schölkopf, B. In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics, 38:847-855, JMLR Workshop and Conference Proceedings, (Editors: Lebanon, G. and Vishwanathan, S.V.N.), JMLR.org, AISTATS, 2015 (Published) Web PDF BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Probabilistic Line Searches for Stochastic Optimization Mahsereci, M., Hennig, P. In Advances in Neural Information Processing Systems 28, 181-189, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), 2015 (Published) Matlab research code URL BibTeX

Perceiving Systems Empirical Inference Probabilistic Numerics Conference Paper Probabilistic Progress Bars Kiefel, M., Schuler, C., Hennig, P. In Conference on Pattern Recognition (GCPR), 8753:331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, GCPR, September 2014 website+code pdf DOI BibTeX

Perceiving Systems Empirical Inference Probabilistic Numerics Conference Paper Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics Hennig, P., Hauberg, S. In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33:347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, AISTATS, April 2014 pdf Youtube Supplements BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Active Learning of Linear Embeddings for Gaussian Processes Garnett, R., Osborne, M., Hennig, P. In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, 230-239, (Editors: NL Zhang and J Tian), AUAI Press , Corvallis, Oregon, UAI2014, 2014, another link: http://arxiv.org/abs/1310.6740 PDF Web BibTeX

Autonomous Motion Empirical Inference Probabilistic Numerics Conference Paper Efficient Bayesian Local Model Learning for Control Meier, F., Hennig, P., Schaal, S. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems, 2244 - 2249, IROS, 2014, clmc PDF DOI URL BibTeX

Autonomous Motion Empirical Inference Probabilistic Numerics Conference Paper Incremental Local Gaussian Regression Meier, F., Hennig, P., Schaal, S. In Advances in Neural Information Processing Systems 27, 972-980, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), 2014, clmc PDF URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers Schober, M., Kasenburg, N., Feragen, A., Hennig, P., Hauberg, S. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, Lecture Notes in Computer Science Vol. 8675, 265-272, (Editors: P. Golland, N. Hata, C. Barillot, J. Hornegger and R. Howe), Springer, Heidelberg, MICCAI, 2014 DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Probabilistic ODE Solvers with Runge-Kutta Means Schober, M., Duvenaud, D., Hennig, P. In Advances in Neural Information Processing Systems 27, 739-747, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), 2014 (Published) Web URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature Gunter, T., Osborne, M., Garnett, R., Hennig, P., Roberts, S. In Advances in Neural Information Processing Systems 27, 2789-2797, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), 2014 (Published) Web URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Analytical probabilistic proton dose calculation and range uncertainties Bangert, M., Hennig, P., Oelfke, U. In 17th International Conference on the Use of Computers in Radiation Therapy, 6-11, (Editors: A. Haworth and T. Kron), ICCR, 2013 BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Fast Probabilistic Optimization from Noisy Gradients Hennig, P. In Proceedings of The 30th International Conference on Machine Learning, JMLR W&CP 28(1), 62–70, (Editors: S Dasgupta and D McAllester), ICML, 2013 PDF BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Nonparametric dynamics estimation for time periodic systems Klenske, E., Zeilinger, M., Schölkopf, B., Hennig, P. In Proceedings of the 51st Annual Allerton Conference on Communication, Control, and Computing, 486-493 , 2013 PDF DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper The Randomized Dependence Coefficient Lopez-Paz, D., Hennig, P., Schölkopf, B. In Advances in Neural Information Processing Systems 26, 1-9, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS 2013), 2013 PDF BibTeX

Perceiving Systems Empirical Inference Probabilistic Numerics Conference Paper Quasi-Newton Methods: A New Direction Hennig, P., Kiefel, M. In Proceedings of the 29th International Conference on Machine Learning, 25-32, ICML ’12, (Editors: John Langford and Joelle Pineau), Omnipress, New York, NY, USA, ICML, July 2012 website+code pdf URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Learning Tracking Control with Forward Models Bócsi, B., Hennig, P., Csató, L., Peters, J. In 259 -264, IEEE International Conference on Robotics and Automation (ICRA 2012), May 2012 PDF Web DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Approximate Gaussian Integration using Expectation Propagation Cunningham, J., Hennig, P., Lacoste-Julien, S. In 1-11, -, January 2012 (Submitted) Web BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Kernel Topic Models Hennig, P., Stern, D., Herbrich, R., Graepel, T. In Fifteenth International Conference on Artificial Intelligence and Statistics, 22:511-519, JMLR Proceedings, (Editors: Lawrence, N. D. and Girolami, M.), JMLR.org, AISTATS 2012 , 2012 PDF Web BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Optimal Reinforcement Learning for Gaussian Systems Hennig, P. In Advances in Neural Information Processing Systems 24, 325-333, (Editors: J Shawe-Taylor and RS Zemel and P Bartlett and F Pereira and KQ Weinberger), Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), 2011 PDF Web BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Using an Infinite Von Mises-Fisher Mixture Model to Cluster Treatment Beam Directions in External Radiation Therapy Bangert, M., Hennig, P., Oelfke, U. In 746-751 , (Editors: Draghici, S. , T.M. Khoshgoftaar, V. Palade, W. Pedrycz, M.A. Wani, X. Zhu), IEEE, Piscataway, NJ, USA, Ninth International Conference on Machine Learning and Applications (ICMLA 2010), December 2010 Web DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Coherent Inference on Optimal Play in Game Trees Hennig, P., Stern, D., Graepel, T. In JMLR Workshop and Conference Proceedings Volume 9: AISTATS 2010, 326-333, (Editors: Teh, Y.W. , M. Titterington ), JMLR, Cambridge, MA, USA, Thirteenth International Conference on Artificial Intelligence and Statistics, May 2010 PDF Web BibTeX