130 results
(View BibTeX file of all listed publications)

**Temporal Difference Models: Model-Free Deep RL for Model-Based Control**
*6th International Conference on Learning Representations (ICLR)*, May 2018, *equal contribution (conference)

**Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders**
*Workshop at the 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning**
*6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Tempered Adversarial Networks**
*Workshop at the 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Learning Coupled Forward-Inverse Models with Combined Prediction Errors**
*IEEE International Conference on Robotics and Automation, (ICRA)*, pages: 2433-2439, IEEE, May 2018 (conference)

**Learning Disentangled Representations with Wasserstein Auto-Encoders**
*Workshop at the 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Automatic Estimation of Modulation Transfer Functions**
*IEEE International Conference on Computational Photography (ICCP)*, May 2018 (conference)

**Causal Discovery Using Proxy Variables**
*Workshop at 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences**
*IEEE International Conference on Robotics and Automation, (ICRA)*, pages: 596-601, IEEE, May 2018 (conference)

**Group invariance principles for causal generative models**
*Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS)*, 84, pages: 557-565, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

**Boosting Variational Inference: an Optimization Perspective**
*Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS)*, 84, pages: 464-472, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

**Cause-Effect Inference by Comparing Regression Errors**
*Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) *, 84, pages: 900-909, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

**Will People Like Your Image? Learning the Aesthetic Space**
*2018 IEEE Winter Conference on Applications of Computer Vision (WACV)*, pages: 2048-2057, March 2018 (conference)

**Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation**
*Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM)*, pages: 324-332, (Editors: Yi Chang, Chengxiang Zhai, Yan Liu, and Yoelle Maarek), ACM, Febuary 2018 (conference)

**Functional Programming for Modular Bayesian Inference**
*Proceedings of the ACM on Functional Programming (ICFP)*, 2(Article No. 83):1-29, ACM, 2018 (conference)

**Automatic Bayesian Density Analysis**
2018 (conference) Submitted

Babbar, R., Schölkopf, B.
**Adversarial Extreme Multi-label Classification**
2018 (conference) Submitted

**k–SVRG: Variance Reduction for Large Scale Optimization**
In 2018 (inproceedings) Submitted

**Probabilistic Deep Learning using Random Sum-Product Networks**
2018 (conference) Submitted

**A Differentially Private Kernel Two-Sample Test**
2018, *equal contribution (conference) Submitted

**Counterfactuals uncover the modular structure of deep generative models**
2018 (conference) Submitted

**Denotational Validation of Higher-order Bayesian Inference**
*Proceedings of the ACM on Principles of Programming Languages (POPL)*, 2(Article No. 60):1-29, ACM, 2018 (conference)

**Conformal Multi-Instance Kernels**
In *NIPS 2006 Workshop on Learning to Compare Examples*, pages: 1-6, NIPS Workshop on Learning to Compare Examples, December 2006 (inproceedings)

**A Kernel Method for the Two-Sample-Problem**
20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)

**Ab-initio gene finding using machine learning**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Graph boosting for molecular QSAR analysis**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Inferring Causal Directions by Evaluating the Complexity of Conditional Distributions**
NIPS Workshop on Causality and Feature Selection, December 2006 (talk)

**Learning Optimal EEG Features Across Time, Frequency and Space**
NIPS Workshop on Current Trends in Brain-Computer Interfacing, December 2006 (talk)

**Semi-Supervised Learning**
Advanced Methods in Sequence Analysis Lectures, November 2006 (talk)

**Adapting Spatial Filter Methods for Nonstationary BCIs**
In *IBIS 2006*, pages: 65-70, 2006 Workshop on Information-Based Induction Sciences, November 2006 (inproceedings)

**A Machine Learning Approach for Determining the PET Attenuation Map from Magnetic Resonance Images**
IEEE Medical Imaging Conference, November 2006 (talk)

**Semi-Supervised Support Vector Machines and Application to Spam Filtering**
ECML Discovery Challenge Workshop, September 2006 (talk)

**A Linear Programming Approach for Molecular QSAR analysis**
In *MLG 2006*, pages: 85-96, (Editors: Gärtner, T. , G. C. Garriga, T. Meinl), International Workshop on Mining and Learning with Graphs, September 2006, Best Paper Award (inproceedings)

**Incremental Aspect Models for Mining Document Streams**
In *PKDD 2006*, pages: 633-640, (Editors: Fürnkranz, J. , T. Scheffer, M. Spiliopoulou), Springer, Berlin, Germany, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, September 2006 (inproceedings)

**PALMA: Perfect Alignments using Large Margin Algorithms**
In *GCB 2006*, pages: 104-113, (Editors: Huson, D. , O. Kohlbacher, A. Lupas, K. Nieselt, A. Zell), Gesellschaft für Informatik, Bonn, Germany, German Conference on Bioinformatics, September 2006 (inproceedings)

**Graph Based Semi-Supervised Learning with Sharper Edges**
In *ECML 2006*, pages: 401-412, (Editors: Fürnkranz, J. , T. Scheffer, M. Spiliopoulou), Springer, Berlin, Germany, 17th European Conference on Machine Learning (ECML), September 2006 (inproceedings)

**Semi-Supervised Learning**
pages: 508, Adaptive computation and machine learning, MIT Press, Cambridge, MA, USA, September 2006 (book)

**Finite-Horizon Optimal State-Feedback Control of Nonlinear Stochastic Systems Based on a Minimum Principle**
In *MFI 2006*, pages: 371-376, (Editors: Hanebeck, U. D.), IEEE Service Center, Piscataway, NJ, USA, 6th IEEE International Conference on Multisensor Fusion and Integration, September 2006 (inproceedings)

**Uniform Convergence of Adaptive Graph-Based Regularization**
In *COLT 2006*, pages: 50-64, (Editors: Lugosi, G. , H.-U. Simon), Springer, Berlin, Germany, 19th Annual Conference on Learning Theory, September 2006 (inproceedings)

**Regularised CSP for Sensor Selection in BCI**
In *Proceedings of the 3rd International Brain-Computer Interface Workshop and Training Course 2006*, pages: 14-15, (Editors: GR Müller-Putz and C Brunner and R Leeb and R Scherer and A Schlögl and S Wriessnegger and G Pfurtscheller), Verlag der Technischen Universität Graz, Graz, Austria, 3rd International Brain-Computer Interface Workshop and Training Course, September 2006 (inproceedings)

**Time-Dependent Demixing of Task-Relevant EEG Signals**
In *Proceedings of the 3rd International Brain-Computer Interface Workshop and Training Course 2006*, pages: 20-21, (Editors: GR Müller-Putz and C Brunner and R Leeb and R Scherer and A Schlögl and S Wriessnegger and G Pfurtscheller), Verlag der Technischen Universität Graz, Graz, Austria, 3rd International Brain-Computer Interface Workshop and Training Course, September 2006 (inproceedings)

**Inferential Structure Determination: Probabilistic determination and validation of NMR structures**
Gordon Research Conference on Computational Aspects of Biomolecular
NMR, September 2006 (talk)

**A Sober Look at Clustering Stability**
In *COLT 2006*, pages: 5-19, (Editors: Lugosi, G. , H.-U. Simon), Springer, Berlin, Germany, 19th Annual Conference on Learning Theory, September 2006 (inproceedings)

**Information Marginalization on Subgraphs**
In *ECML/PKDD 2006*, pages: 199-210, (Editors: Fürnkranz, J. , T. Scheffer, M. Spiliopoulou), Springer, Berlin, Germany, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, September 2006 (inproceedings)

**Bayesian Active Learning for Sensitivity Analysis**
In *ECML 2006*, pages: 353-364, (Editors: Fürnkranz, J. , T. Scheffer, M. Spiliopoulou), Springer, Berlin, Germany, 17th European Conference on Machine Learning, September 2006 (inproceedings)

**Machine Learning Algorithms for Polymorphism Detection**
2nd ISCB Student Council Symposium, August 2006 (talk)

**Supervised Probabilistic Principal Component Analysis**
In *KDD 2006*, pages: 464-473, (Editors: Ungar, L. ), ACM Press, New York, NY, USA, 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2006 (inproceedings)

**Inferential structure determination: Overview and new developments**
Sixth CCPN Annual Conference: Efficient and Rapid Structure Determination by NMR, July 2006 (talk)

**A Continuation Method for Semi-Supervised SVMs**
In *ICML 2006*, pages: 185-192, (Editors: Cohen, W. W., A. Moore), ACM Press, New York, NY, USA, 23rd International Conference on Machine Learning, June 2006 (inproceedings)

**MCMC inference in (Conditionally) Conjugate Dirichlet Process Gaussian Mixture Models**
ICML Workshop on Learning with Nonparametric Bayesian Methods, June 2006 (talk)