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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 Article Probabilistic Interpretation of Linear Solvers Hennig, P. SIAM Journal on Optimization, 25(1):234-260, 2015 (Published) Web PDF DOI URL 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
Empirical Inference Probabilistic Numerics Article Probabilistic numerics and uncertainty in computations Hennig, P., Osborne, M. A., Girolami, M. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 471(2179), 2015 (Published) PDF DOI 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
Autonomous Motion Probabilistic Numerics Miscellaneous Local Gaussian Regression Meier, F., Hennig, P., Schaal, S. arXiv preprint, March 2014, clmc Web URL 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 Thesis Camera-specific Image Denoising Schober, M. Eberhard Karls Universität Tübingen, Germany, October 2013 (Published) PDF BibTeX
Perceiving Systems Empirical Inference Probabilistic Numerics Article Quasi-Newton Methods: A New Direction Hennig, P., Kiefel, M. Journal of Machine Learning Research, 14(1):843-865, March 2013 website+code pdf URL BibTeX
Empirical Inference Probabilistic Numerics Article Analytical probabilistic modeling for radiation therapy treatment planning Bangert, M., Hennig, P., Oelfke, U. Physics in Medicine and Biology, 58(16):5401-5419, 2013 PDF DOI 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 Technical Report Animating Samples from Gaussian Distributions Hennig, P. (8), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2013 PDF 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
Empirical Inference Probabilistic Numerics Poster The Randomized Dependence Coefficient Lopez-Paz, D., Hennig, P., Schölkopf, B. 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 Article Entropy Search for Information-Efficient Global Optimization Hennig, P., Schuler, C. Journal of Machine Learning Research, 13:1809-1837, -, June 2012 PDF Web 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 Thesis Nonparametric System Identification and Control for Periodic Error Correction in Telescopes Klenske, E. D. University of Stuttgart, 2012 (Published) PDF 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