Office: S2.006

Max-Planck-Ring 4

72076 Tübingen

Germany

Max-Planck-Ring 4

72076 Tübingen

Germany

+49 7071 601 572

+49 7071 601 552

On 1 May 2018, I was appointed as a Full Professor to the newly created Chair for the Methods of Machine Learning at the Computer Science department of the University of Tübingen. **Please find my new page there.** I am also keeping an adjunct position at the Max Planck Institute for Intelligent Systems.

Inference Probability Numerical Methods

75 results
(View BibTeX file of all listed publications)

**Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers**
In *Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, Lecture Notes in Computer Science Vol. 8675*, pages: 265-272, (Editors: P. Golland, N. Hata, C. Barillot, J. Hornegger and R. Howe), Springer, Heidelberg, MICCAI, 2014 (inproceedings)

**Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature**
In *Advances in Neural Information Processing Systems 27*, pages: 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 (inproceedings)

**Incremental Local Gaussian Regression**
In *Advances in Neural Information Processing Systems 27*, pages: 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, clmc (inproceedings)

**Efficient Bayesian Local Model Learning for Control**
In *Proceedings of the IEEE International Conference on Intelligent Robots and Systems*, pages: 2244 - 2249, IROS, 2014, clmc (inproceedings)

**Quasi-Newton Methods: A New Direction**
*Journal of Machine Learning Research*, 14(1):843-865, March 2013 (article)

**The Randomized Dependence Coefficient**
In *Advances in Neural Information Processing Systems 26*, pages: 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 (inproceedings)

**Fast Probabilistic Optimization from Noisy Gradients**
In *Proceedings of The 30th International Conference on Machine Learning, JMLR W&CP 28(1)*, pages: 62–70, (Editors: S Dasgupta and D McAllester), ICML, 2013 (inproceedings)

**Nonparametric dynamics estimation for time periodic systems**
In *Proceedings of the 51st Annual Allerton Conference on Communication, Control, and Computing*, pages: 486-493 , 2013 (inproceedings)

**The Randomized Dependence Coefficient**
Neural Information Processing Systems (NIPS), 2013 (poster)

**Analytical probabilistic modeling for radiation therapy treatment planning**
*Physics in Medicine and Biology*, 58(16):5401-5419, 2013 (article)

**Analytical probabilistic proton dose calculation and range uncertainties**
In *17th International Conference on the Use of Computers in Radiation Therapy*, pages: 6-11, (Editors: A. Haworth and T. Kron), ICCR, 2013 (inproceedings)

**Animating Samples from Gaussian Distributions**
(8), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2013 (techreport)

**Quasi-Newton Methods: A New Direction**
In *Proceedings of the 29th International Conference on Machine Learning*, pages: 25-32, ICML ’12, (Editors: John Langford and Joelle Pineau), Omnipress, New York, NY, USA, ICML, July 2012 (inproceedings)

**Entropy Search for Information-Efficient Global Optimization**
*Journal of Machine Learning Research*, 13, pages: 1809-1837, -, June 2012 (article)

**Learning Tracking Control with Forward Models**
In pages: 259 -264, IEEE International Conference on Robotics and Automation (ICRA), May 2012 (inproceedings)

**Approximate Gaussian Integration using Expectation Propagation**
In pages: 1-11, -, January 2012 (inproceedings) Submitted

**Kernel Topic Models**
In *Fifteenth International Conference on Artificial Intelligence and Statistics*, 22, pages: 511-519, JMLR Proceedings, (Editors: Lawrence, N. D. and Girolami, M.), JMLR.org, AISTATS , 2012 (inproceedings)

**Optimal Reinforcement Learning for Gaussian Systems**
In *Advances in Neural Information Processing Systems 24*, pages: 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 (inproceedings)

**Using an Infinite Von Mises-Fisher Mixture Model to Cluster Treatment Beam Directions in External Radiation Therapy **
In pages: 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), December 2010 (inproceedings)

**Approximate Inference in Graphical Models**
University of Cambridge, November 2010 (phdthesis)

**Coherent Inference on Optimal Play in Game Trees**
In *JMLR Workshop and Conference Proceedings Volume 9: AISTATS 2010*, pages: 326-333, (Editors: Teh, Y.W. , M. Titterington ), JMLR, Cambridge, MA, USA, Thirteenth International Conference on Artificial Intelligence and Statistics, May 2010 (inproceedings)

**Bayesian Quadratic Reinforcement Learning**
NIPS Workshop on Probabilistic Approaches for Robotics and Control, December 2009 (poster)

**Expectation Propagation on the Maximum of Correlated Normal Variables**
Cavendish Laboratory: University of Cambridge, July 2009 (techreport)

**Point-spread functions for backscattered imaging in the scanning electron microscope **
*Journal of Applied Physics *, 102(12):1-8, December 2007 (article)

**Classified Regression for Bayesian Optimization: Robot Learning with Unknown Penalties**
Submitted to Journal (article) In preparation