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Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

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Social Foundations of Computation

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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

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Robot Learning

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2022

Autonomous Learning

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Probabilistic Numerics Conference Paper Active Uncertainty Calibration in Bayesian ODE Solvers Kersting, H., Hennig, P. Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), 309-318, (Editors: Ihler, Alexander T. and Janzing, Dominik), June 2016 (Published) URL 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
Probabilistic Numerics Conference Paper Batch Bayesian Optimization via Local Penalization González, J., Dai, Z., Hennig, P., Lawrence, N. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51:648-657, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C.), May 2016 (Published) URL BibTeX
Probabilistic Numerics Conference Paper Probabilistic Approximate Least-Squares Bartels, S., Hennig, P. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51:676-684, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C. ), May 2016 (Published) URL BibTeX
Empirical Inference Probabilistic Numerics Article Dual Control for Approximate Bayesian Reinforcement Learning Klenske, E. D., Hennig, P. Journal of Machine Learning Research, 17(127):1-30, 2016 (Published) PDF URL BibTeX
Empirical Inference Probabilistic Numerics Article Gaussian Process-Based Predictive Control for Periodic Error Correction Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P. IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (Published) PDF DOI 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