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Autonomous Motion Probabilistic Numerics Intelligent Control Systems Conference Paper On the Design of LQR Kernels for Efficient Controller Learning Marco, A., Hennig, P., Schaal, S., Trimpe, S. Proceedings of the 56th IEEE Annual Conference on Decision and Control (CDC), 5193-5200, IEEE, IEEE Conference on Decision and Control, December 2017 (Published) arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI BibTeX
Probabilistic Numerics Article Probabilistic Line Searches for Stochastic Optimization Mahsereci, M., Hennig, P. Journal of Machine Learning Research, 18(119):1-59, November 2017 (Published) URL BibTeX
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
Empirical Inference Probabilistic Numerics Conference Paper Dynamic Time-of-Flight Schober, M., Adam, A., Yair, O., Mazor, S., Nowozin, S. Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, 170-179, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (Published) DOI 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
Probabilistic Numerics Conference Paper Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets Klein, A., Falkner, S., Bartels, S., Hennig, P., Hutter, F. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 54:528-536, Proceedings of Machine Learning Research, (Editors: Sign, Aarti and Zhu, Jerry), PMLR, April 2017 (Published) pdf URL BibTeX
Probabilistic Numerics Article Analytical probabilistic modeling of RBE-weighted dose for ion therapy Wieser, H., Hennig, P., Wahl, N., Bangert, M. Physics in Medicine and Biology (PMB), 62(23):8959-8982, 2017 URL BibTeX
Probabilistic Numerics Perceiving Systems Article Early Stopping Without a Validation Set Mahsereci, M., Balles, L., Lassner, C., Hennig, P. arXiv preprint arXiv:1703.09580, 2017 URL BibTeX
Probabilistic Numerics Article Efficiency of analytical and sampling-based uncertainty propagation in intensity-modulated proton therapy Wahl, N., Hennig, P., Wieser, H. P., Bangert, M. Physics in Medicine & Biology, 62(14):5790-5807, 2017 URL BibTeX
Probabilistic Numerics Article Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning Roos, F. D., Hennig, P. arXiv preprint arXiv:1706.00241, 2017 URL BibTeX
Empirical Inference Probabilistic Numerics Article New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481) Gretton, A., Hennig, P., Rasmussen, C., Schölkopf, B. Dagstuhl Reports, 6(11):142-167, 2017 (Published) DOI BibTeX
Empirical Inference Probabilistic Numerics Software Workshop Ph.D. Thesis Nonparametric Disturbance Correction and Nonlinear Dual Control Klenske, E. D. (24098), ETH Zurich, 2017 DOI BibTeX
Empirical Inference Probabilistic Numerics Miscellaneous Probabilistic Active Learning of Functions in Structural Causal Models Rubenstein, P. K., Tolstikhin, I., Hennig, P., Schölkopf, B. 2017 (Published) Arxiv BibTeX