77 results
(View BibTeX file of all listed publications)

**Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism**
*53rd Annual Allerton Conference on Communication, Control, and Computing*, September 2015 (talk)

**Kernel methods in medical imaging**
In *Handbook of Biomedical Imaging*, pages: 63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (inbook)

**Independence of cause and mechanism in brain networks**
*DALI workshop on Networks: Processes and Causality*, April 2015 (talk)

**Information-Theoretic Implications of Classical and Quantum Causal Structures **
18th Conference on Quantum Information Processing (QIP), 2015 (talk)

**Assessment of brain tissue damage in the Sub-Acute Stroke Region by Multiparametric Imaging using [89-Zr]-Desferal-EPO-PET/MRI**
World Molecular Imaging Conference, 2015 (talk)

**Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data**
In *Visualization and Processing of Higher Order Descriptors for Multi-Valued Data*, pages: 299-319, (Editors: Hotz, I. and Schultz, T.), Springer, 2015 (inbook)

**Early time point in vivo PET/MR is a promising biomarker for determining efficacy of a novel Db(\alphaEGFR)-scTRAIL fusion protein therapy in a colon cancer model**
World Molecular Imaging Conference, 2015 (talk)

**Justifying Information-Geometric Causal Inference**
In *Measures of Complexity: Festschrift for Alexey Chervonenkis*, pages: 253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (inbook)

**The search for single exoplanet transits in the Kepler light curves**
*IAU General Assembly*, 22, pages: 2258352, 2015 (talk)

**Unsupervised identification of neural events in local field potentials**
44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

**Quantifying statistical dependency**
Research Network on Learning Systems Summer School, 2014 (talk)

**Single-Source Domain Adaptation with Target and Conditional Shift**
In *Regularization, Optimization, Kernels, and Support Vector Machines*, pages: 427-456, 19, Chapman & Hall/CRC Machine Learning & Pattern Recognition, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), Chapman and Hall/CRC, Boca Raton, USA, 2014 (inbook)

**Higher-Order Tensors in Diffusion Imaging**
In *Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data*, pages: 129-161, Mathematics + Visualization, (Editors: Westin, C.-F., Vilanova, A. and Burgeth, B.), Springer, 2014 (inbook)

**Fuzzy Fibers: Uncertainty in dMRI Tractography**
In *Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization*, pages: 79-92, 8, Mathematics + Visualization, (Editors: Hansen, C. D., Chen, M., Johnson, C. R., Kaufman, A. E. and Hagen, H.), Springer, 2014 (inbook)

**Nonconvex Proximal Splitting with Computational Errors**
In *Regularization, Optimization, Kernels, and Support Vector Machines*, pages: 83-102, 4, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), CRC Press, 2014 (inbook)

**Active Learning - Modern Learning Theory**
In *Encyclopedia of Algorithms*, (Editors: Kao, M.-Y.), Springer Berlin Heidelberg, 2014 (incollection)

**Using a population based Gaussian Mixture Model on fused [18]F-FDG PET and DW-MRI images accurately segments the tumor microenvironment into clinically relevant compartments capable of guiding therapy**
European Molecular Imaging Meeting, 2014 (talk)

**Causal Inference from Passive Observations**
24th Summer School University of Jyväskylā, Finland, August, 2014 (talk)

**Support Vector Machines, Support Measure Machines, and Quasar Target Selection**
Center for Cosmology and Particle Physics (CCPP), New York University, December 2012 (talk)

**Hilbert Space Embedding for Dirichlet Process Mixtures**
NIPS Workshop on Confluence between Kernel Methods and Graphical Models, December 2012 (talk)

**Simultaneous small animal PET/MR in activated and resting state reveals multiple brain networks**
20th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2012 (talk)

**A new PET insert for simultaneous PET/MR small animal imaging**
20th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2012 (talk)

**Evaluation of a new, large field of view, small animal PET/MR system**
50. Jahrestagung der Deutschen Gesellschaft fuer Nuklearmedizin (NuklearMedizin), April 2012 (talk)

**Expectation-Maximization methods for solving (PO)MDPs and optimal control problems**
In *Inference and Learning in Dynamic Models*, (Editors: Barber, D., Cemgil, A.T. and Chiappa, S.), Cambridge University Press, Cambridge, UK, January 2012 (inbook) In press

**Active Learning Methods in Classification of Remote Sensing Images**
In *Signal and Image Processing for Remote Sensing*, (Editors: CH Chen), CRC Press, Boca Raton, FL, USA, January 2012 (inbook) In press

**Simultaneous small animal PET/MR reveals different brain networks during stimulation and rest**
World Molecular Imaging Congress (WMIC), 2012 (talk)

Muandet, K.
**Support Measure Machines for Quasar Target Selection**
Astro Imaging Workshop, 2012 (talk)

**PAC-Bayesian Analysis: A Link Between Inference and Statistical Physics
**
Workshop on Statistical Physics of Inference and Control Theory, 2012 (talk)

**PET Performance Measurements of a Next Generation Dedicated Small Animal PET/MR Scanner**
Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), 2012 (talk)

**Inferential structure determination from NMR data**
In *Bayesian methods in structural bioinformatics*, pages: 287-312, (Editors: Hamelryck, T., Mardia, K. V. and Ferkinghoff-Borg, J.), Springer, New York, 2012 (inbook)

**Robot Learning**
In *Encyclopedia of the sciences of learning*, (Editors: Seel, N.M.), Springer, Berlin, Germany, 2012 (inbook)

**Reinforcement Learning in Robotics: A Survey**
In *Reinforcement Learning*, 12, pages: 579-610, (Editors: Wiering, M. and Otterlo, M.), Springer, Berlin, Germany, 2012 (inbook)

**PAC-Bayesian Analysis of Supervised, Unsupervised, and Reinforcement Learning
**
Tutorial at the 29th International Conference on Machine Learning (ICML), 2012 (talk)

**Influence of MR-based attenuation correction on lesions within bone and susceptibility artifact regions**
Molekulare Bildgebung (MoBi), 2012 (talk)

**Structured Apprenticeship Learning**
European Workshop on Reinforcement Learning (EWRL), 2012 (talk)

**PAC-Bayesian Analysis and Its Applications**
Tutorial at The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2012 (talk)

**Solving Nonlinear Continuous State-Action-Observation POMDPs for Mechanical Systems with Gaussian Noise
**
European Workshop on Reinforcement Learning (EWRL), 2012 (talk)

**Kernel Bellman Equations in POMDPs**
Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML'12), 2012 (talk)

**Higher-Order Tensors in Diffusion MRI**
In *Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data*, (Editors: Westin, C. F., Vilanova, A. and Burgeth, B.), Springer, 2012 (inbook) Accepted

**Beta oscillations propagate as traveling waves in the macaque prefrontal cortex**
42nd Annual Meeting of the Society for Neuroscience (Neuroscience), 2012 (talk)

**Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Positional Oligomer Importance Matrices**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Machine Learning Algorithms for Polymorphism Detection**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**An Automated Combination of Kernels for Predicting Protein Subcellular Localization**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Challenges in Brain-Computer Interface Development: Induction, Measurement, Decoding, Integration**
Invited keynote talk at the launch of BrainGain, the Dutch BCI research consortium, November 2007 (talk)

**Policy Learning for Robotics**
14th International Conference on Neural Information Processing (ICONIP), November 2007 (talk)

**Hilbert Space Representations of Probability Distributions**
2nd Workshop on Machine Learning and Optimization at the ISM, October 2007 (talk)

**Regression with Intervals**
International Workshop on Data-Mining and Statistical Science (DMSS2007), October 2007, JSAI Incentive Award. Talk was given by Hisashi Kashima. (talk)

**Support Vector Machine Learning for Interdependent and Structured Output Spaces**
In *Predicting Structured Data*, pages: 85-104, Advances in neural information processing systems, (Editors: Bakir, G. H. , T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V. N. Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)