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Tronarp, F., Kersting, H., Särkkä, S., Hennig, P.
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective
ArXiv preprint 2018, arXiv:1810.03440 [stat.ME], October 2018 (article)
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Kersting, H., Sullivan, T. J., Hennig, P.
Convergence Rates of Gaussian ODE Filters
arXiv preprint 2018, arXiv:1807.09737 [math.NA], July 2018 (article)
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Stutz, D., Geiger, A.
Learning 3D Shape Completion under Weak Supervision
Arxiv, May 2018 (article)
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Kanagawa, M., Hennig, P., Sejdinovic, D., Sriperumbudur, B. K.
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)
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Alhaija, H., Mustikovela, S., Mescheder, L., Geiger, A., Rother, C.
Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes
International Journal of Computer Vision (IJCV), 2018, 2018 (article)
ei
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Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S.
Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference
Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)
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Nishiyama, Y., Kanagawa, M., Gretton, A., Fukumizu, K.
Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models
Arxiv e-prints, arXiv:1409.5178v2 [stat.ML], 2018 (article)
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Schober, M., Särkkä, S., Philipp Hennig,
A probabilistic model for the numerical solution of initial value problems
Statistics and Computing, Springer US, 2018 (article)
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Wahl, N., Hennig, P., Wieser, H., Bangert, M.
Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity-modulated proton therapy
Medical Physics, 2018 (article)
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Stutz, D., Geiger, A.
Learning 3D Shape Completion under Weak Supervision
International Journal of Computer Vision (IJCV), 2018, 2018 (article)
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Menze, M., Heipke, C., Geiger, A.
Object Scene Flow
ISPRS Journal of Photogrammetry and Remote Sensing, 2018 (article)
ei
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Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P.
Gaussian Process-Based Predictive Control for Periodic Error Correction
IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)
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Klenske, E. D., Hennig, P.
Dual Control for Approximate Bayesian Reinforcement Learning
Journal of Machine Learning Research, 17(127):1-30, 2016 (article)
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Mescheder, L., Nowozin, S., Geiger, A.
Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring
Arxiv, 2016 (article)
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Brubaker, M. A., Geiger, A., Urtasun, R.
Map-Based Probabilistic Visual Self-Localization
IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)
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Geiger, A., Lenz, P., Stiller, C., Urtasun, R.
Vision meets Robotics: The KITTI Dataset
International Journal of Robotics Research, 32(11):1231 - 1237 , Sage Publishing, September 2013 (article)
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Hennig, P., Kiefel, M.
Quasi-Newton Methods: A New Direction
Journal of Machine Learning Research, 14(1):843-865, March 2013 (article)
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Bangert, M., Hennig, P., Oelfke, U.
Analytical probabilistic modeling for radiation therapy treatment planning
Physics in Medicine and Biology, 58(16):5401-5419, 2013 (article)