450 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

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

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

Mastakouri, A. A., Schölkopf, B.
**Causal analysis of Covid-19 spread in Germany**
2020 (misc) Submitted

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

**Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem**
In 59th IEEE Conference on Decision and Control (CDC), 2020 (inproceedings) Accepted

**Advances in Latent Variable and Causal Models**
University of Cambridge, UK, 2020, (Cambridge-Tuebingen-Fellowship) (phdthesis)

**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

**Causal Discovery from Heterogeneous/Nonstationary Data**
*Journal of Machine Learning Research*, 21(89):1-53, 2020 (article)

**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)

**BCPy2000**
Workshop "Machine Learning Open-Source Software" at NIPS, December 2008 (talk)

**Stereo Matching for Calibrated Cameras without Correspondence**
In *CDC 2008*, pages: 2408-2413, IEEE Service Center, Piscataway, NJ, USA, 47th IEEE Conference on Decision and Control, December 2008 (inproceedings)

**Joint Kernel Support Estimation for Structured Prediction**
In *Proceedings of the NIPS 2008 Workshop on "Structured Input - Structured Output" (NIPS SISO 2008)*, pages: 1-4, NIPS Workshop on "Structured Input - Structured Output" (NIPS SISO), December 2008 (inproceedings)

**A Predictive Model for Imitation Learning in Partially Observable Environments**
In *ICMLA 2008*, pages: 83-90, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. A. Kurgan, T. Hu, K. Hafeez), IEEE, Piscataway, NJ, USA, Seventh International Conference on Machine Learning and Applications, December 2008 (inproceedings)

**Frequent Subgraph Retrieval in Geometric Graph Databases**
In *ICDM 2008*, pages: 953-958, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, 8th IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Block Iterative Algorithms for Non-negative Matrix Approximation**
In *ICDM 2008*, pages: 1037-1042, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Service Center, Piscataway, NJ, USA, Eighth IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Metropolis Algorithms for Representative Subgraph Sampling**
In pages: 283-292, (Editors: Giannotti, F.), IEEE, Piscataway, NJ, USA, Eighth IEEE International Conference on Data Mining (ICDM '08) , December 2008 (inproceedings)

**A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation**
In *ICMLA 2008*, pages: 3-9, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. Kurgan, T. Hu, K. Hafeez), IEEE Computer Society, Los Alamitos, CA, USA, 7th International Conference on Machine Learning and Applications, December 2008 (inproceedings)

**Infinite Kernel Learning**
In *Proceedings of the NIPS 2008 Workshop on "Kernel Learning: Automatic Selection of Optimal Kernels"*, pages: 1-4, NIPS Workshop on "Kernel Learning: Automatic Selection of Optimal Kernels" (LK ASOK´08), December 2008 (inproceedings)

**Logistic Regression for Graph Classification**
NIPS Workshop on "Structured Input - Structured Output" (NIPS SISO), December 2008 (talk)

**New Projected Quasi-Newton Methods with Applications**
Microsoft Research Tech-talk, December 2008 (talk)

**Prediction-Directed Compression of POMDPs**
In *ICMLA 2008*, pages: 99-105, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. A. Kurgan, T. Hu, K. Hafeez), IEEE, Piscataway, NJ, USA, Seventh International Conference on Machine Learning and Applications, December 2008 (inproceedings)

**Iterative Subgraph Mining for Principal Component Analysis**
In *ICDM 2008*, pages: 1007-1012, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Modelling contrast discrimination data suggest both the pedestal effect and stochastic resonance to be caused by the same mechanism**
*Journal of Vision*, 8(15):1-21, November 2008 (article)