443 results
(View BibTeX file of all listed publications)

**Kernel Conditional Moment Test via Maximum Moment Restriction**
*Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI)*, August 2020 (conference) Accepted

**Bayesian Online Prediction of Change Points**
*Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI)*, August 2020 (conference) Accepted

**Algorithmic Recourse: from Counterfactual Explanations to Interventions**
*37th International Conference on Machine Learning (ICML)*, July 2020 (conference) Submitted

**Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control**
*21rst IFAC World Congress*, July 2020 (conference) Accepted

**A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming**
*21rst IFAC World Congress*, July 2020 (conference) Accepted

**Model-Agnostic Counterfactual Explanations for Consequential Decisions**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, June 2020 (conference) Accepted

**A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, June 2020 (conference) Accepted

**Kernel Conditional Density Operators**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, Proceedings of Machine Learning Research, June 2020 (conference) Accepted

**A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control**
*2nd Annual Conference on Learning for Dynamics and Control (L4DC)*, June 2020 (conference) Accepted

**Disentangling Factors of Variations Using Few Labels**
*8th International Conference on Learning Representations (ICLR)*, April 2020 (conference)

**Mixed-curvature Variational Autoencoders**
*8th International Conference on Learning Representations (ICLR)*, April 2020 (conference)

**Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals**
*ICLR 2020 Workshop "Tackling Climate Change with Machine Learning"*, April 2020 (conference)

**An Open Force-Controlled Modular Robot Architecture for Legged Locomotion Research**
*The IEEE Robotics and Automation Letters*, 5(2):3650 - 3657, IEEE, April 2020 (article)

**From Variational to Deterministic Autoencoders**
*8th International Conference on Learning Representations (ICLR) *, April 2020, *equal contribution (conference) Accepted

**On Mutual Information Maximization for Representation Learning**
*8th International Conference on Learning Representations (ICLR)*, April 2020 (conference) Accepted

**Towards causal generative scene models via competition of experts**
*ICLR 2020 Workshop "Causal Learning for Decision Making"*, April 2020, *equal contribution (conference)

**Adaptation and Robust Learning of Probabilistic Movement Primitives**
*IEEE Transactions on Robotics*, 36(2):366-379, IEEE, March 2020 (article)

**Real Time Trajectory Prediction Using Deep Conditional Generative Models**
*IEEE Robotics and Automation Letters*, 5(2):970-976, IEEE, January 2020 (article)

**More Powerful Selective Kernel Tests for Feature Selection **
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2020 (conference) To be published

**Computationally Tractable Riemannian Manifolds for Graph Embeddings**
*37th International Conference on Machine Learning (ICML)*, 2020 (conference) Submitted

**Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem**
2020 (misc) Submitted

**A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models **
*IEEE International Conference on Robotics and Automation (ICRA)*, 2020 (conference) Accepted

**An Adaptive Optimizer for Measurement-Frugal Variational Algorithms**
*Quantum*, 4, pages: 263, 2020 (article)

**Practical Accelerated Optimization on Riemannian Manifolds**
*37th International Conference on Machine Learning (ICML)*, 2020 (conference) Submitted

**Fair Decisions Despite Imperfect Predictions**
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2020 (conference) Accepted

**Counterfactual Mean Embedding**
*Journal of Machine Learning Research*, 2020 (article) Accepted

**Learning to Play Table Tennis From Scratch using Muscular Robots**
2020 (article) Submitted

**Constant Curvature Graph Convolutional Networks**
*37th International Conference on Machine Learning (ICML)*, 2020, *equal contribution (conference) Submitted

**Testing Goodness of Fit of Conditional Density Models with Kernels**
2020 (misc) Submitted

**Divide-and-Conquer Monte Carlo Tree Search for goal directed planning**
2020, *equal contribution (conference) Submitted

**A machine learning route between band mapping and band structure**
2020, *equal contribution (misc)

**Camera-specific Image Denoising**
Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

**Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI**
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)

**Correlation of Simultaneously Acquired Diffusion-Weighted Imaging and 2-Deoxy-[18F] fluoro-2-D-glucose Positron Emission Tomography of Pulmonary Lesions in a Dedicated Whole-Body Magnetic Resonance/Positron Emission Tomography System**
*Investigative Radiology*, 48(5):247-255, May 2013 (article)

**Replacing Causal Faithfulness with Algorithmic Independence of Conditionals**
*Minds and Machines*, 23(2):227-249, May 2013 (article)

**What can neurons do for their brain? Communicate selectivity with bursts**
*Theory in Biosciences *, 132(1):27-39, Springer, March 2013 (article)

**Apprenticeship Learning with Few Examples**
*Neurocomputing*, 104, pages: 83-96, March 2013 (article)

**Quasi-Newton Methods: A New Direction**
*Journal of Machine Learning Research*, 14(1):843-865, March 2013 (article)

**Regional effects of magnetization dispersion on quantitative perfusion imaging for pulsed and continuous arterial spin labeling**
*Magnetic Resonance in Medicine*, 69(2):524-530, Febuary 2013 (article)

**The multivariate Watson distribution: Maximum-likelihood estimation and other aspects**
*Journal of Multivariate Analysis*, 114, pages: 256-269, February 2013 (article)

**How the result of graph clustering methods depends on the construction of the graph**
*ESAIM: Probability & Statistics*, 17, pages: 370-418, January 2013 (article)

**Falsification and future performance**
In *Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence*, 7070, pages: 65-78, Lecture Notes in Computer Science, Springer, Berlin, Germany, Solomonoff 85th Memorial Conference, January 2013 (inproceedings)

**How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?**
*PLoS Computational Biology*, 9(1):e1002873, January 2013 (article)

**Explicit eigenvalues of certain scaled trigonometric matrices**
*Linear Algebra and its Applications*, 438(1):173-181, January 2013 (article)

**A neural population model for visual pattern detection**
*Psychological Review*, 120(3):472–496, 2013 (article)

**Feedback Error Learning for Rhythmic Motor Primitives**
In *Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA 2013)*, pages: 1317-1322, 2013 (inproceedings)

**Gaussian Process Vine Copulas for Multivariate Dependence**
In *Proceedings of the 30th International Conference on Machine Learning, W&CP 28(2)*, pages: 10-18, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013, Poster:
http://people.tuebingen.mpg.de/dlopez/papers/icml2013_gpvine_poster.pdf (inproceedings)

**A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs)**
In *Brain-Computer Interface Research*, pages: 39-51, 4, SpringerBriefs in Electrical and Computer Engineering, (Editors: Guger, C., Allison, B. Z. and Edlinger, G.), Springer, 2013 (inbook)