383 results
(View BibTeX file of all listed publications)

**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)

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

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

**The Randomized Dependence Coefficient**
In *Advances in Neural Information Processing Systems 26*, pages: 1-9, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**On a link between kernel mean maps and Fraunhofer diffraction, with an application to super-resolution beyond the diffraction limit**
In *IEEE Conference on Computer Vision and Pattern Recognition*, pages: 1083-1090, IEEE, CVPR, 2013 (inproceedings)

**Output Kernel Learning Methods**
In *International Workshop on Advances in Regularization,
Optimization, Kernel Methods and Support Vector Machines: theory and applications*, ROKS, 2013 (inproceedings)

**Alignment-based Transfer Learning for Robot Models**
In *Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013)*, pages: 1-7, 2013 (inproceedings)

**Accurate indel prediction using paired-end short reads**
*BMC Genomics*, 14(132), 2013 (article)

**Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method**
In *13th International Conference on Data Mining*, pages: 1003-1008, (Editors: H. Xiong, G. Karypis, B. M. Thuraisingham, D. J. Cook and X. Wu), IEEE Computer Society, ICDM, 2013 (inproceedings)

**A probabilistic approach to robot trajectory generation**
In *Proceedings of the 13th IEEE International Conference on Humanoid Robots (HUMANOIDS)*, pages: 477-483, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

**Geometric optimisation on positive definite matrices for elliptically contoured distributions**
In *Advances in Neural Information Processing Systems 26*, pages: 2562-2570, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Coupling between spiking activity and beta band spatio-temporal patterns in the macaque PFC**
43rd Annual Meeting of the Society for Neuroscience (Neuroscience), 2013 (poster)

**Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising**
*Journal of Machine Learning Research*, 14, pages: 3207-3260, 2013 (article)

**Fast Probabilistic Optimization from Noisy Gradients**
In *Proceedings of The 30th International Conference on Machine Learning, JMLR W&CP 28(1)*, pages: 62–70, (Editors: S Dasgupta and D McAllester), ICML, 2013 (inproceedings)

**Structure and Dynamics of Information Pathways in On-line Media**
In *6th ACM International Conference on Web Search and Data Mining (WSDM)*, pages: 23-32, (Editors: S Leonardi, A Panconesi, P Ferragina, and A Gionis), ACM, WSDM, 2013 (inproceedings)

**Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments**
In *Proceedings of the Tenth European Workshop on Reinforcement Learning *, pages: 103-116, (Editors: MP Deisenroth and C Szepesvári and J Peters), JMLR, EWRL, 2013 (inproceedings)

**Gaussian Process Vine Copulas for Multivariate Dependence**
International Conference on Machine Learning (ICML), 2013 (poster)

**Domain adaptation under Target and Conditional Shift**
In *Proceedings of the 30th International Conference on Machine Learning, W&CP 28 (3)*, pages: 819–827, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013 (inproceedings)

**From Ordinary Differential Equations to Structural Causal Models: the deterministic case **
In *Proceedings of the Twenty-Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence*, pages: 440-448, (Editors: A Nicholson and P Smyth), AUAI Press, Corvallis, Oregon, UAI, 2013 (inproceedings)

**A machine learning approach for non-blind image deconvolution**
In *IEEE Conference on Computer Vision and Pattern Recognition*, pages: 1067-1074, IEEE, CVPR, 2013 (inproceedings)

**Domain Generalization via Invariant Feature Representation**
30th International Conference on Machine Learning (ICML2013), 2013 (poster)

**When luminance increment thresholds depend on apparent lightness**
*Journal of Vision*, 13(6):1-11, 2013 (article)

**Autonomous Reinforcement Learning with Hierarchical REPS**
In *Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013)*, pages: 1-8, 2013 (inproceedings)

**Efficient network-guided multi-locus association mapping with graph cuts**
*Bioinformatics*, 29(13):i171-i179, 2013 (article)

**Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry**
In *Information Processing in Medical Imaging*, pages: 171-183, (Editors: JC Gee and S Joshi and KM Pohl and WM Wells and L Zöllei), Springer, Berlin Heidelberg, 23rd International Conference on Information Processing in Medical Imaging (IPMI), 2013, Lecture Notes in Computer Science, Vol. 7017 (inproceedings)

**On estimation of functional causal models: Post-nonlinear causal model as an example**
In *First IEEE ICDM workshop on causal discovery *, 2013, Held in conjunction with the 12th IEEE International Conference on Data Mining (ICDM 2013) (inproceedings)

**Object Modeling and Segmentation by Robot Interaction with Cluttered Environments**
In *Proceedings of the IEEE International Conference on Humanoid Robots (HUMANOIDS)*, pages: 169-176, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

**Reflection methods for user-friendly submodular optimization**
In *Advances in Neural Information Processing Systems 26*, pages: 1313-1321, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Semi-supervised learning in causal and anticausal settings**
In *Empirical Inference*, pages: 129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)

**Analyzing locking of spikes to spatio-temporal patterns in the macaque prefrontal cortex**
Bernstein Conference, 2013 (poster)

**On Flat versus Hierarchical Classification in Large-Scale Taxonomies**
In *Advances in Neural Information Processing Systems 26*, pages: 1824-1832, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Quantifying causal influences**
*Annals of Statistics*, 41(5):2324-2358, 2013 (article)

**Probabilistic movement modeling for intention inference in human-robot interaction
**
*International Journal of Robotics Research*, 32(7):841-858, 2013 (article)

**Blind Retrospective Motion Correction of MR Images**
*Magnetic Resonance in Medicine (MRM)*, 70(6):1608–1618, 2013 (article)

**Modeling fixation locations using spatial point processes**
*Journal of Vision*, 13(12):1-34, 2013 (article)

**Tractable large-scale optimization in machine learning**
In *Tractability: Practical Approaches to Hard Problems*, pages: 202-230, 7, (Editors: Bordeaux, L., Hamadi , Y., Kohli, P. and Mateescu, R. ), Cambridge University Press , 2013 (inbook)