Publications

Intelligent Control Systems Movement Generation and Control Probabilistic Numerics Empirical Inference Article Robot Learning with Crash Constraints Marco, A., Baumann, D., Khadiv, M., Hennig, P., Righetti, L., Trimpe, S. IEEE Robotics and Automation Letters, 6(2):1439-1446, IEEE, February 2021 (Published) DOI URL BibTeX

Probabilistic Numerics Article Three-dimensional models of core-collapse supernovae from low-mass progenitors with implications for Crab Stockinger, G., Janka, H., Kresse, D., Melson, T., Ertl, T., Gabler, M., Gessner, A., Wongwathanarat, A., Tolstov, A., Leung, S., et al. Monthly Notices of the Royal Astronomical Society , 496(2):2039-2084, August 2020 (Published) DOI BibTeX

Probabilistic Numerics Article Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings Kanagawa, M., Sriperumbudur, B. K., Fukumizu, K. Foundations of Computational Mathematics, 20:155-1944, February 2020 (Published) arXiv DOI BibTeX

Empirical Inference Probabilistic Numerics Article Analytical probabilistic modeling of dose-volume histograms Wahl, N., Hennig, P., Wieser, H., Bangert, M. Medical Physics, 47(10):5260-5273, 2020 (Published) DOI BibTeX

Empirical Inference Probabilistic Numerics Article Convergence rates of Gaussian ODE filters Kersting, H., Sullivan, T. J., Hennig, P. Statistics and Computing, 30(6):1791-1816, 2020 (Published) DOI BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Convergence Guarantees for Adaptive Bayesian Quadrature Methods Kanagawa, M., Hennig, P. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :6234-6245, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Limitations of the empirical Fisher approximation for natural gradient descent Kunstner, F., Hennig, P., Balles, L. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :4158-4169, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Probabilistic Numerics Article Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective Tronarp, F., Kersting, H., Särkkä, S., Hennig, P. Statistics and Computing, 29(6):1297-1315, 2019 (Published) DOI URL BibTeX

Probabilistic Numerics Conference Paper Active Multi-Information Source Bayesian Quadrature Gessner, A. G. J. M. M. Proceedings 35TH UNCERTAINTY IN ARTIFICIAL INTELLIGENCE CONFERENCE (UAI 2019), :712-721, (Editors: Adams, RP; Gogate, V), UAI, July 2019 (Published) URL BibTeX

Probabilistic Numerics Empirical Inference Conference Paper DeepOBS: A Deep Learning Optimizer Benchmark Suite Schneider, F., Balles, L., Hennig, P. 7th International Conference on Learning Representations (ICLR), May 2019 (Published) URL BibTeX

Probabilistic Numerics Empirical Inference Conference Paper Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization de Roos, F., Hennig, P. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:1448-1457, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF URL BibTeX

Probabilistic Numerics Empirical Inference Conference Paper Fast and Robust Shortest Paths on Manifolds Learned from Data Arvanitidis, G., Hauberg, S., Hennig, P., Schober, M. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89:1506-1515, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (Published) PDF URL BibTeX

Empirical Inference Probabilistic Numerics Article Dense connectomic reconstruction in layer 4 of the somatosensory cortex Motta, A., Berning, M., Boergens, K. M., Staffler, B., Beining, M., Loomba, S., Hennig, P., Wissler, H., Helmstaedter, M. Science, 366(6469):eaay3134, 2019 (Published) DOI BibTeX

Probabilistic Numerics Article On the positivity and magnitudes of Bayesian quadrature weights Karvonen, T., Kanagawa, M., Särkä, S. Statistics and Computing, 29:1317-1333, 2019 (Published) DOI BibTeX

Probabilistic Numerics Article Probabilistic Linear Solvers: A Unifying View Bartels, S., Cockayne, J., Ipsen, I., Hennig, P. Statistics and Computing, 29(6):1249-1263, 2019 (Published) DOI URL BibTeX

Empirical Inference Probabilistic Numerics Article Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective Tronarp, F., Kersting, H., Särkkä, S. H. P. Statistics and Computing, 29(6):1297-1315, 2019 (Published) DOI BibTeX

Probabilistic Numerics Conference Paper Kernel Recursive ABC: Point Estimation with Intractable Likelihood Kajihara, T., Kanagawa, M., Yamazaki, K., Fukumizu, K. Proceedings of the 35th International Conference on Machine Learning, :2405-2414, PMLR, July 2018 () Paper BibTeX

Probabilistic Numerics Article Convergence Rates of Gaussian ODE Filters Kersting, H., Sullivan, T. J., Hennig, P. arXiv preprint 2018, arXiv:1807.09737 [math.NA], July 2018 () URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S. Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (CausalML) at ICML, July 2018 (Published) BibTeX

Probabilistic Numerics Conference Paper Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients Balles, L., Hennig, P. Proceedings of the 35th International Conference on Machine Learning (ICML), 80:404-413, Proceedings of Machine Learning Research, (Editors: Jennifer Dy and Andreas Krause), PMLR, ICML, July 2018 (Published) URL BibTeX

Probabilistic Numerics Article A probabilistic model for the numerical solution of initial value problems Schober, M., Särkkä, S., Hennig, P. Statistics and Computing, 29(1):99–122, 2018 (Published) PDF Code DOI BibTeX

Probabilistic Numerics Article Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity-modulated proton therapy Wahl, N., Hennig, P., Wieser, H., Bangert, M. Medical Physics, 45(4):1317-1328, 2018 (Published) DOI BibTeX

Probabilistic Numerics Empirical Inference Article Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S. Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 () arXiv BibTeX

Probabilistic Numerics Article Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Kanagawa, M., Hennig, P., Sejdinovic, D., Sriperumbudur, B. K. Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 () arXiv BibTeX

Empirical Inference Probabilistic Numerics Statistical Learning Theory Miscellaneous Large sample analysis of the median heuristic Garreau, D., Jitkrittum, W., Kanagawa, M. 2018, In preparation (In preparation) arXiv BibTeX

Probabilistic Numerics Article Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models Nishiyama, Y., Kanagawa, M., Gretton, A., Fukumizu, K. Arxiv e-prints, arXiv:1409.5178v2 [stat.ML], 2018 () arXiv BibTeX

Empirical Inference Probabilistic Numerics Ph.D. Thesis Probabilistic Approaches to Stochastic Optimization Mahsereci, M. Eberhard Karls Universität Tübingen, Germany, 2018 (Published) URL BibTeX

Empirical Inference Probabilistic Numerics Ph.D. Thesis Probabilistic Ordinary Differential Equation Solvers — Theory and Applications Schober, M. Eberhard Karls Universität Tübingen, Germany, 2018 (Published) BibTeX

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

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

Autonomous Motion Empirical Inference Probabilistic Numerics Intelligent Control Systems Conference Paper Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S. Machine Learning in Planning and Control of Robot Motion Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS), Machine Learning in Planning and Control of Robot Motion Workshop, October 2015 (Published) 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

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