19 results
(View BibTeX file of all listed publications)

**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)

**Kernel Recursive ABC: Point Estimation with Intractable Likelihood**
*Proceedings of the 35th International Conference on Machine Learning*, pages: 2405-2414, PMLR, July 2018 (conference)

**Convergence Rates of Gaussian ODE Filters**
*arXiv preprint 2018*, arXiv:1807.09737 [math.NA], July 2018 (article)

**Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference**
*Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (CausalML) at ICML*, July 2018 (conference)

**Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences**
*Arxiv e-prints*, arXiv:1805.08845v1 [stat.ML], 2018 (article)

**Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients**
In *Proceedings of the 35th International Conference on Machine Learning (ICML)*, 2018 (inproceedings) Accepted

**Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference**
*Arxiv e-prints*, arXiv:1805.08845v1 [stat.ML], 2018 (article)

**Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models**
*Arxiv e-prints*, arXiv:1409.5178v2 [stat.ML], 2018 (article)

**A probabilistic model for the numerical solution of initial value problems**
*Statistics and Computing*, Springer US, 2018 (article)

**Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity-modulated proton therapy**
*Medical Physics*, 2018 (article)

**Probabilistic Approaches to Stochastic Optimization**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**Large sample analysis of the median heuristic**
2018 (misc) In preparation

**Probabilistic Ordinary Differential Equation Solvers — Theory and Applications**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**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)

**Nonparametric System Identification and Control for Periodic Error Correction in Telescopes**
University of Stuttgart, 2012 (diplomathesis)