Zhang, K., Hyvärinen, A.
Nonlinear functional causal models for distinguishing cause from effect
In Statistics and Causality: Methods for Applied Empirical Research, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)
Castaneda, S., Katiyar, P., Russo, F., Calaminus, C., Disselhorst, J. A., Ziemann, U., Kohlhofer, U., Quintanilla-Martinez, L., Poli, S., Pichler, B. J.
Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke
World Molecular Imaging Conference, 2016 (talk)
Hohmann, M., Fomina, T., Jayaram, V., Widmann, N., Förster, C., Just, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.
A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis
In Brain-Computer Interfaces: Lab Experiments to Real-World Applications, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)
Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J., Disselhorst, J. A.
Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy
World Molecular Imaging Conference, 2016 (talk)
Besserve, M.
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)
Charpiat, G., Hofmann, M., Schölkopf, B.
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)
Besserve, M.
Independence of cause and mechanism in brain networks
DALI workshop on Networks: Processes and Causality, April 2015 (talk)
Chaves, R., Majenz, C., Luft, L., Maciel, T., Janzing, D., Schölkopf, B., Gross, D.
Information-Theoretic Implications of Classical and Quantum Causal Structures
18th Conference on Quantum Information Processing (QIP), 2015 (talk)
Castaneda, S. G., Katiyar, P., Russo, F., Disselhorst, J. A., Calaminus, C., Poli, S., Maurer, A., Ziemann, U., Pichler, B. J.
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)
O’Donnell, L. J., Schultz, T.
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)
Divine, M. R., Harant, M., Katiyar, P., Disselhorst, J. A., Bukala, D., Aidone, S., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J.
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)
Janzing, D., Steudel, B., Shajarisales, N., Schölkopf, B.
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)
Foreman-Mackey, D., Hogg, D. W., Schölkopf, B.
The search for single exoplanet transits in the Kepler light curves
IAU General Assembly, 22, pages: 2258352, 2015 (talk)
Schmidt, M., Kim, D., Sra, S.
Projected Newton-type methods in machine learning
In Optimization for Machine Learning, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)
Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T.
Combined whole-body PET/MR imaging: MR contrast agents do not affect the quantitative accuracy of PET following attenuation correction
(SST15-05 ), 97th Scientific Assemble and Annual Meeting of the Radiological Society of North America (RSNA), December 2011 (talk)
Jegelka, S.
Cooperative Cuts: a new use of submodularity in image segmentation
Second I.S.T. Austria Symposium on Computer Vision and Machine Learning, October 2011 (talk)
Lois, C., Bezrukov, I., Schmidt, H., Schwenzer, N., Werner, M., Pichler, B., Kupferschläger, J., Beyer, T.
Effect of MR Contrast Agents on Quantitative Accuracy of PET in Combined Whole-Body PET/MR Imaging
2011(MIC3-3), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)
Schmidt, H., Schwenzer, N., Bezrukov, I., Kolb, A., Mantlik, F., Kupferschläger, J., Lois, C., Sauter, A., Brendle, C., Pfannenberg, C., Pichler, B.
First Results on Patients and Phantoms of a Fully Integrated Clinical Whole-Body PET/MRI
2011(J2-8), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)
Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T.
Effect of MR contrast agents on quantitative accuracy of PET in combined whole-body PET/MR imaging
(OP314), Annual Congress of the European Association of Nuclear Medicine (EANM), October 2011 (talk)
Sauter, A., Schmidt, H., Gueckel, B., Brendle, C., Bezrukov, I., Mantlik, F., Kolb, A., Mueller, M., Reimold, M., Federmann, B., Hetzel, J., Claussen, C., Pfannenberg, C., Horger, M., Pichler, B., Schwenzer, N.
Multi-parametric Tumor Characterization and Therapy Monitoring using Simultaneous PET/MRI: initial results for Lung Cancer and GvHD
(T110), 2011 World Molecular Imaging Congress (WMIC), September 2011 (talk)
Langovoy, M., Habeck, M., Schölkopf, B.
Statistical Image Analysis and Percolation Theory
2011 Joint Statistical Meetings (JSM), August 2011 (talk)
von Luxburg, U., Schölkopf, B.
Statistical Learning Theory: Models, Concepts, and Results
In Handbook of the History of Logic, Vol. 10: Inductive Logic, 10, pages: 651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 (inbook)
Jegelka, S.
Cooperative Cuts
COSA Workshop: Combinatorial Optimization, Statistics, and Applications, March 2011 (talk)
Peters, J., Tedrake, R., Roy, N., Morimoto, J.
Robot Learning
In Encyclopedia of Machine Learning, pages: 865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 (inbook)
Ihme, K., Zander, TO.
What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI
In Affective Computing and Intelligent Interaction, 6975, pages: 447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 (inbook)
Borgwardt, KM.
Kernel Methods in Bioinformatics
In Handbook of Statistical Bioinformatics, pages: 317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 (inbook)
Rosas, P., Wichmann, F.
Cue Combination: Beyond Optimality
In Sensory Cue Integration, pages: 144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 (inbook)
Zhou, D.
Spectral clustering and transductive inference for graph data
NIPS Workshop on Kernel Methods and Structured Domains, December 2005 (talk)
Chapelle, O.
Some thoughts about Gaussian Processes
NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)
Chapelle, O.
A taxonomy of semi-supervised learning algorithms
Yahoo!, December 2005 (talk)
Wu, M., Schölkopf, B., BakIr, G.
Building Sparse Large Margin Classifiers
The 22nd International Conference on Machine Learning (ICML), August 2005 (talk)
Zhou, D.
Learning from Labeled and Unlabeled Data on a Directed Graph
The 22nd International Conference on Machine Learning, August 2005 (talk)
Bensch, M., Bogdan, M., Hill, N., Lal, T., Rosenstiel, W., Schölkopf, B., Schröder, M.
Machine-Learning Approaches to BCI in Tübingen
Brain-Computer Interface Technology, June 2005, Talk given by NJH. (talk)
Peters, J., Schaal, S.
Learning Motor Primitives with Reinforcement Learning
ROBOTICS Workshop on Modular Foundations for Control and Perception, June 2005 (talk)
Peters, J.
Motor Skill Learning for Humanoid Robots
First Conference Undergraduate Computer Sciences and Informations Sciences (CS/IS), May 2005 (talk)
Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Belitski, A., Augath, M., Murayama, Y., Schölkopf, B., Logothetis, N.
Kernel Constrained Covariance for Dependence Measurement
AISTATS, January 2005 (talk)
Schölkopf, B., Smola, A.
Support Vector Machines and Kernel Algorithms
In Encyclopedia of Biostatistics (2nd edition), Vol. 8, 8, pages: 5328-5335, (Editors: P Armitage and T Colton), John Wiley & Sons, NY USA, 2005 (inbook)
Wagemans, J., Wichmann, F., de Beeck, H.
Visual perception
I: Basic principles
In Handbook of Cognition, pages: 3-47, (Editors: Lamberts, K. , R. Goldstone), Sage, London, 2005 (inbook)
Dahmen, H-J., Franz, MO., Krapp, HG.
Extracting egomotion from optic flow: limits of accuracy and neural matched filters
In pages: 143-168, Springer, Berlin, 2001 (inbook)
Schölkopf, B., Smola, A., Müller, K., Burges, C., Vapnik, V.
Support Vector methods in learning and feature extraction
Ninth Australian Conference on Neural Networks, pages: 72-78, (Editors: T. Downs, M. Frean and M. Gallagher), 1998 (talk)
Schölkopf, B.
Support-Vektor-Lernen
In Ausgezeichnete Informatikdissertationen 1997, pages: 135-150, (Editors: G Hotz and H Fiedler and P Gorny and W Grass and S Hölldobler and IO Kerner and R Reischuk), Teubner Verlag, Stuttgart, 1998 (inbook)