Publications

Empirical Inference Book Chapter Natural Language Processing for Policymaking Jin, Z., Mihalcea, R. In Handbook of Computational Social Science for Policy, :141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (Published) DOI BibTeX

Empirical Inference Book Chapter CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z. In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, :69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (Published) DOI BibTeX

Empirical Inference Book Chapter Causal Models for Dynamical Systems Peters, J., Bauer, S., Pfister, N. In Probabilistic and Causal Inference: The Works of Judea Pearl, :671-690, 1, Association for Computing Machinery, 2022 (Published) arXiv DOI BibTeX

Empirical Inference Book Chapter Causality for Machine Learning Schölkopf, B. In Probabilistic and Causal Inference: The Works of Judea Pearl, :765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (Published) arXiv DOI BibTeX

Empirical Inference Probabilistic Learning Group Book Chapter Towards Causal Algorithmic Recourse Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I. In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, :139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (Published) DOI BibTeX

Empirical Inference Book Chapter Methods in Psychophysics Wichmann, F. A., Jäkel, F. In Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (Published) BibTeX

Empirical Inference Book Chapter Policy Gradient Methods Peters, J., Bagnell, J. In Encyclopedia of Machine Learning and Data Mining, :982-985, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (Published) URL BibTeX

Empirical Inference Autonomous Motion Book Chapter Robot Learning Peters, J., Lee, D., Kober, J., Nguyen-Tuong, D., Bagnell, J., Schaal, S. In Springer Handbook of Robotics, :357-394, 15, 2nd, (Editors: Siciliano, Bruno and Khatib, Oussama), Springer International Publishing, 2017 (Published) BibTeX

Empirical Inference Book Chapter Robot Learning Peters, J., Tedrake, R., Roy, N., Morimoto, J. In Encyclopedia of Machine Learning and Data Mining, :1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (Published) DOI BibTeX

Empirical Inference Book Chapter Statistical Asymmetries Between Cause and Effect Janzing, D. In Time in Physics, :129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (Published) DOI URL BibTeX

Empirical Inference Book Chapter Unsupervised clustering of EOG as a viable substitute for optical eye-tracking Flad, N., Fomina, T., Bülthoff, H. H., Chuang, L. L. In First Workshop on Eye Tracking and Visualization (ETVIS 2015), :151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (Published) DOI BibTeX

Empirical Inference Book Chapter Nonlinear functional causal models for distinguishing cause from effect Zhang, K., Hyvärinen, A. In Statistics and Causality: Methods for Applied Empirical Research, :185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (Published) BibTeX

Empirical Inference Book Chapter Kernel methods in medical imaging Charpiat, G., Hofmann, M., Schölkopf, B. In Handbook of Biomedical Imaging, :63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (Published) Web URL BibTeX

Empirical Inference Book Chapter Justifying Information-Geometric Causal Inference Janzing, D., Steudel, B., Shajarisales, N., Schölkopf, B. In Measures of Complexity: Festschrift for Alexey Chervonenkis, :253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (Published) DOI BibTeX

Empirical Inference Book Chapter Fuzzy Fibers: Uncertainty in dMRI Tractography Schultz, T., Vilanova, A., Brecheisen, R., Kindlmann, G. In Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization, :79-92, 8, Mathematics + Visualization, (Editors: Hansen, C. D., Chen, M., Johnson, C. R., Kaufman, A. E. and Hagen, H.), Springer, 2014 (Published) BibTeX

Empirical Inference Book Chapter Higher-Order Tensors in Diffusion Imaging Schultz, T., Fuster, A., Ghosh, A., Deriche, R., Florack, L., Lim, L. In Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data, :129-161, Mathematics + Visualization, (Editors: Westin, C.-F., Vilanova, A. and Burgeth, B.), Springer, 2014 (Published) BibTeX

Empirical Inference Book Chapter Nonconvex Proximal Splitting with Computational Errors Sra, S. In Regularization, Optimization, Kernels, and Support Vector Machines, :83-102, 4, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), CRC Press, 2014 (Published) BibTeX

Empirical Inference Book Chapter Single-Source Domain Adaptation with Target and Conditional Shift Zhang, K., Schölkopf, B., Muandet, K., Wang, Z., Zhou, Z., Persello, C. In Regularization, Optimization, Kernels, and Support Vector Machines, :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 () BibTeX

Empirical Inference Book Chapter A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs) Grosse-Wentrup, M., Schölkopf, B. In Brain-Computer Interface Research, :39-51, 4, SpringerBriefs in Electrical and Computer Engineering, (Editors: Guger, C., Allison, B. Z. and Edlinger, G.), Springer, 2013 () PDF DOI BibTeX

Empirical Inference Book Chapter On the Relations and Differences between Popper Dimension, Exclusion Dimension and VC-Dimension Seldin, Y., Schölkopf, B. In Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, :53-57, 6, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (Published) BibTeX

Empirical Inference Book Chapter Semi-supervised learning in causal and anticausal settings Schölkopf, B., Janzing, D., Peters, J., Sgouritsa, E., Zhang, K., Mooij, J. In Empirical Inference, :129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 () DOI BibTeX

Empirical Inference Book Chapter Tractable large-scale optimization in machine learning Sra, S. In Tractability: Practical Approaches to Hard Problems, :202-230, 7, (Editors: Bordeaux, L., Hamadi , Y., Kohli, P. and Mateescu, R. ), Cambridge University Press , 2013 (Published) BibTeX

Empirical Inference Book Chapter Expectation-Maximization methods for solving (PO)MDPs and optimal control problems Toussaint, M., Storkey, A., Harmeling, S. In Inference and Learning in Dynamic Models, (Editors: Barber, D., Cemgil, A.T. and Chiappa, S.), Cambridge University Press, Cambridge, UK, January 2012, In press (In press) PDF BibTeX

Empirical Inference Book Chapter Higher-Order Tensors in Diffusion MRI Schultz, T., Fuster, A., Ghosh, A., Deriche, R., Florack, L., Lim, L. 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, Accepted (Accepted) BibTeX

Empirical Inference Book Chapter Inferential structure determination from NMR data Habeck, M. In Bayesian methods in structural bioinformatics, :287-312, (Editors: Hamelryck, T., Mardia, K. V. and Ferkinghoff-Borg, J.), Springer, New York, 2012 () BibTeX

Empirical Inference Book Chapter Reinforcement Learning in Robotics: A Survey Kober, J., Peters, J. In Reinforcement Learning, 12:579-610, (Editors: Wiering, M. and Otterlo, M.), Springer, Berlin, Germany, 2012 () Web DOI BibTeX

Empirical Inference Book Chapter Robot Learning Sigaud, O., Peters, J. In Encyclopedia of the sciences of learning, (Editors: Seel, N.M.), Springer, Berlin, Germany, 2012 () Web BibTeX

Empirical Inference Book Chapter Projected Newton-type methods in machine learning Schmidt, M., Kim, D., Sra, S. In Optimization for Machine Learning, :305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 () PDF Web BibTeX

Empirical Inference Book Chapter Statistical Learning Theory: Models, Concepts, and Results von Luxburg, U., Schölkopf, B. In Handbook of the History of Logic, Vol. 10: Inductive Logic, 10:651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 () PDF Web DOI BibTeX

Empirical Inference Book Chapter Robot Learning Peters, J., Tedrake, R., Roy, N., Morimoto, J. In Encyclopedia of Machine Learning, :865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 () PDF Web DOI BibTeX

Empirical Inference Book Chapter Cue Combination: Beyond Optimality Rosas, P., Wichmann, F. In Sensory Cue Integration, :144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 () BibTeX

Empirical Inference Book Chapter Kernel Methods in Bioinformatics Borgwardt, K. In Handbook of Statistical Bioinformatics, :317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 () PDF DOI BibTeX

Empirical Inference Book Chapter What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI Ihme, K., Zander, T. In Affective Computing and Intelligent Interaction, 6975:447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 () DOI BibTeX

Empirical Inference Book Chapter Markerless tracking of Dynamic 3D Scans of Faces Walder, C., Breidt, M., Bülthoff, H., Schölkopf, B., Curio, C. In Dynamic Faces: Insights from Experiments and Computation, :255-276, (Editors: Curio, C., Bülthoff, H. H. and Giese, M. A.), MIT Press, Cambridge, MA, USA, December 2010 () Web BibTeX

Empirical Inference Book Chapter Policy Gradient Methods Peters, J., Bagnell, J. In Encyclopedia of Machine Learning, :774-776, (Editors: Sammut, C. and Webb, G. I.), Springer, Berlin, Germany, December 2010 () PDF Web DOI BibTeX

Empirical Inference Book Chapter From Motor Learning to Interaction Learning in Robots Sigaud, O., Peters, J. In From Motor Learning to Interaction Learning in Robots, :1-12, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 () Web DOI BibTeX

Empirical Inference Book Chapter Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling Kober, J., Mohler, B., Peters, J. In From Motor Learning to Interaction Learning in Robots, :209-225, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 () PDF Web DOI BibTeX

Empirical Inference Book Chapter Learning Continuous Grasp Affordances by Sensorimotor Exploration Detry, R., Baseski, E., Popovic, M., Touati, Y., Krüger, N., Kroemer, O., Peters, J., Piater, J. In From Motor Learning to Interaction Learning in Robots, :451-465, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 () PDF Web DOI BibTeX

Empirical Inference Book Chapter Real-Time Local GP Model Learning Nguyen-Tuong, D., Seeger, M., Peters, J. In From Motor Learning to Interaction Learning in Robots, 264:193-207, Studies in Computational Intelligence, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 () PDF Web DOI BibTeX

Empirical Inference Book Chapter Approaches Based on Support Vector Machine to Classification of Remote Sensing Data Bruzzone, L., Persello, C. In Handbook of Pattern Recognition and Computer Vision, :329-352, (Editors: Chen, C.H.), ICP, London, UK, 2010 () Web BibTeX

Empirical Inference Book Chapter Machine Learning Methods for Automatic Image Colorization Charpiat, G., Bezrukov, I., Hofmann, M., Altun, Y., Schölkopf, B. In Computational Photography: Methods and Applications, :395-418, Digital Imaging and Computer Vision, (Editors: Lukac, R.), CRC Press, Boca Raton, FL, USA, 2010 () PDF Web BibTeX

Empirical Inference Book Chapter Text Clustering with Mixture of von Mises-Fisher Distributions Sra, S., Banerjee, A., Ghosh, J., Dhillon, I. In Text mining: classification, clustering, and applications, :121-161, Chapman & Hall/CRC data mining and knowledge discovery series, (Editors: Srivastava, A. N. and Sahami, M.), CRC Press, Boca Raton, FL, USA, June 2009 () Web DOI BibTeX

Empirical Inference Book Chapter Data Mining for Biologists Tsuda, K. In Biological Data Mining in Protein Interaction Networks, :14-27, (Editors: Li, X. and Ng, S.-K.), Medical Information Science Reference, Hershey, PA, USA, May 2009 () Web BibTeX

Empirical Inference Book Chapter Large Margin Methods for Part of Speech Tagging Altun, Y. In Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, :141-160, (Editors: Keshet, J. and Bengio, S.), Wiley, Hoboken, NJ, USA, January 2009 () Web BibTeX

Empirical Inference Book Chapter Covariate shift and local learning by distribution matching Gretton, A., Smola, A., Huang, J., Schmittfull, M., Borgwardt, K., Schölkopf, B. In Dataset Shift in Machine Learning, :131-160, (Editors: Quiñonero-Candela, J., Sugiyama, M., Schwaighofer, A. and Lawrence, N. D.), MIT Press, Cambridge, MA, USA, 2009 () PDF Web BibTeX

Empirical Inference Book Chapter New Frontiers in Characterizing Structure and Dynamics by NMR Nilges, M., Markwick, P., Malliavin, T., Rieping, W., Habeck, M. In Computational Structural Biology: Methods and Applications, :655-680, (Editors: Schwede, T. , M. C. Peitsch), World Scientific, New Jersey, NJ, USA, May 2008 () Web BibTeX

Empirical Inference Book Chapter A Robot System for Biomimetic Navigation: From Snapshots to Metric Embeddings of View Graphs Franz, M., Stürzl, W., Reichardt, W., Mallot, H. In Robotics and Cognitive Approaches to Spatial Mapping, :297-314, Springer Tracts in Advanced Robotics ; 38, (Editors: Jefferies, M.E. , W.-K. Yeap), Springer, Berlin, Germany, 2008 () PDF PDF DOI BibTeX

Empirical Inference Book Chapter Approximation Methods for Gaussian Process Regression Quiñonero-Candela, J., Rasmussen, C., Williams, C. In Large-Scale Kernel Machines, :203-223, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 () PDF Web BibTeX

Empirical Inference Book Chapter Brain-Computer Interfaces for Communication in Paralysis: A Clinical Experimental Approach Hinterberger, T., Nijboer, F., Kübler, A., Matuz, T., Furdea, A., Mochty, U., Jordan, M., Lal, T., Hill, J., Mellinger, J., et al. In Toward Brain-Computer Interfacing, :43-64, Neural Information Processing, (Editors: G. Dornhege and J del R Millán and T Hinterberger and DJ McFarland and K-R Müller), MIT Press, Cambridge, MA, USA, September 2007 () PDF Web BibTeX

Empirical Inference Book Chapter Brisk Kernel ICA Jegelka, S., Gretton, A. In Large Scale Kernel Machines, :225-250, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 () PDF Web BibTeX

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