Researcher Portfolio
Schober, Michael
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, Max Planck Research Group Probabilistic Numerics, Max Planck Institute for Intelligent Systems, Max Planck Society
Researcher Profile
Position: Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society
Position: Max Planck Research Group Probabilistic Numerics, Max Planck Institute for Intelligent Systems, Max Planck Society
Researcher ID: https://pure.mpg.de/cone/persons/resource/persons140737
Publications
: Schober, M., Särkkä, S., & Hennig, P. (2019). A probabilistic model for the numerical solution of initial value problems. Statistics and Computing, 29(1), 99-122. doi:10.1007/s11222-017-9798-7. [PubMan] : Schober, M. (2018). Probabilistic Ordinary Differential Equation Solvers - Theory and Applications. PhD Thesis, Eberhard Karls Universität Tübingen, Tübingen. [PubMan] : Schober, M., Adam, A., Yair, O., Mazor, S., & Nowozin, S. (2017). Dynamic Time-of-Flight. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) (pp. 170-179). Piscataway, NJ: IEEE. doi:10.1109/CVPR.2017.26. [PubMan] : Schober, M., Duvenaud, D., & Hennig, P. (2015). Probabilistic ODE Solvers with Runge-Kutta Means. In Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, & K. Q. Weinberger (Eds. ), Advances in Neural Information Processing Systems 27 (pp. 739-747). Red Hook, NY: Curran Associates, Inc. Retrieved from https://papers.nips.cc/paper/2014/hash/59b90e1005a220e2ebc542eb9d950b1e-Abstract.html. [PubMan] : Hauberg, S., Schober, M., Liptrot, M., Hennig, P., & Feragen, A. (2015). A Random Riemannian Metric for Probabilistic Shortest-Path Tractography. In N. Navab, J. Hornegger, W. Wells, & A. Frangi (Eds. ), Proceedings Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015 (pp. 597-604). Cham: Springer. doi:10.1007/978-3-319-24553-9_73. [PubMan] : Schober, M., Kasenburg, N., Feragen, A., Hennig, P., & Hauberg, S. (2014). Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers. In P. Golland, N. Hata, C. Barillot, J. Hornegger, & R. Howe (Eds. ), Proceedings of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014), Part III (pp. 265-272). Springer International Publishing. doi:10.1007/978-3-319-10443-0_34. [PubMan]