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Journal Article (8)

  1. 1.
    Klenske, E.; Hennig, P.: Dual Control for Approximate Bayesian Reinforcement Learning. The Journal of Machine Learning Research 17 (1), pp. 4354 - 4383 (2016)
  2. 2.
    Klenske, E.; Hennig, P.: Dual Control for Approximate Bayesian Reinforcement Learning. Journal of Machine Learning Research (JMLR) 17 (1), pp. 4354 - 4383 (2016)
  3. 3.
    Klenske, E.; Zeilinger, M.; Schölkopf, B.; Hennig, P.: Gaussian Process Based Predictive Control for Periodic Error Correction. IEEE Transactions on Control Systems Technology 24 (1), pp. 110 - 121 (2016)
  4. 4.
    Hennig, P.; Osborne, M. A.; Girolami, M.: Probabilistic numerics and uncertainty in computations. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (2015)
  5. 5.
    Hennig, P.: Probabilistic Interpretation of Linear Solvers. SIAM Journal on Optimization (2015)
  6. 6.
    Bangert, M.; Hennig, P.; Oelfke, U.: Analytical probabilistic modeling for radiation therapy treatment planning. Physics in Medicine and Biology 58 (16), pp. 5401 - 5419 (2013)
  7. 7.
    Hennig, P.; Kiefel, M.: Quasi-Newton Methods: A New Direction. The Journal of Machine Learning Research 14, pp. 843 - 865 (2013)
  8. 8.
    Hennig, P.; Schuler, C.: Entropy Search for Information-Efficient Global Optimization. Journal of Machine Learning Research 13, pp. 1809 - 1837 (2012)

Conference Paper (20)

  1. 9.
    Bartels, S.; Hennig, P.: Probabilistic Approximate Least-Squares. In: Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016). 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, May 09, 2016 - May 11, 2016. Microtome Publishing, Brookline, MA (2016)
  2. 10.
    Gonzalez, J.; Dai, Z.; Hennig, P.; Lawrence, N.: Batch Bayesian Optimization via Local Penalization. In: Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016) (Eds. Gretton, A.; Robert, C. C.). 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, May 09, 2016 - May 11, 2016. Microtome Publishing, Brookline, MA (2016)
  3. 11.
    Klenske, E.; Hennig, P.; Schölkopf, B.; Zeilinger, M. N.: Approximate dual control maintaining the value of information with an application to building control. In: Proceedings European Control Conference (ECC). European Control Conference, Aalborg, DK, June 29, 2016 - July 01, 2016. IEEE, New York, NY, USA (2016)
  4. 12.
    Marco Valle, A.; Hennig, P.; Bohg, J.; Schaal, S.; Trimpe, S.: Automatic LQR Tuning Based on Gaussian Process Global Optimization. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (Ed. Okamura, A.). 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, May 16, 2016 - May 21, 2016. IEEE, New York, NY, USA (2016)
  5. 13.
    Sgouritsa, E.; Janzing, D.; Hennig, P.; Schoelkopf, B.: Inference of Cause and Effect with Unsupervised Inverse Regression. In: Proceedings of the 18th International Conference on Artificial Intelligence and Statistics. 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 2015, San Diego, CA, USA. Microtome Publishing, Brookline, MA, USA (2015)
  6. 14.
    Bangert, M.; Hennig, P.; Oelfke, U.: Analytical probabilistic proton dose calculation and range uncertainties. XVII International Conference on the Use of Computers in Radiation Therapy, Melbourne, Australia, May 06, 2013 - May 09, 2013. Journal of Physics: Conference Series 489, (2014)
  7. 15.
    Garnett, R.; Osborne, M.; Hennig, P.: Active Learning of Linear Embeddings for Gaussian Processes. In: Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014) (Eds. Zhang, N. L.; Tian, J.). 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), Quebec City, Canada, July 23, 2014 - July 27, 2014. AUAI Press, Corvallis, OR (2014)
  8. 16.
    Gunter, T.; Osborne, M.; Garnett, R.; Hennig, P.; Roberts, S.: Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. In: Advances in Neural Information Processing Systems 27 (NIPS 2014) (Eds. Ghahramani, Z.; Welling, M.; Cortes, C.; Lawrence, N.D.; Weinberger, K.Q.). 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), Montreal, Canada, December 08, 2014 - December 12, 2014. Curran Associates, Inc., Red Hook, NY (2014)
  9. 17.
    Hennig, P.; Hauberg, S.: Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics. In: Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS) (Eds. Kaski, S.; Corander, J.). Seventeenth International Conference on Artificial Intelligence and Statistics, Reykjavik, Iceland, April 22, 2014 - April 25, 2014. (2014)
  10. 18.
    Kiefel, M.; Schuler, C. J.; Hennig, P.: Probabilistic Progress Bars. In: Pattern Recognition. 36th German Conference, GCPR 2014. Proceedings, pp. 331 - 342 (Eds. Xiaoyi, J.; Hornegger, J.; Koch, R.). GCPR 2014. 36th German Conference on Pattern Recognition, Münster, September 02, 2014 - September 05, 2014. Springer International Publishing AG, Cham et al. (2014)
  11. 19.
    Meier, F.; Hennig, P.; Schaal, S.: Efficient Bayesian Local Model Learning for Control. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robotics Systems (IROS 2014). IEEE/RSJ International Conference on Intelligent Robotics Systems (IROS 2014), Chicago, IL, September 14, 2014 - September 18, 2014. IEEE (2014)
  12. 20.
    Meier, F.; Hennig, P.; Schaal, S.: Incremental Local Gaussian Regression. In: Advances in Neural Information Processing Systems 27 (NIPS 2014) (Eds. Ghahramani, Z.; Welling, M.; Cortes, C.; Lawrence, N.D.; Weinberger, K.Q.). 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), Montreal, CA, December 08, 2014 - December 13, 2014. Curran Associates, Inc. (2014)
 
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