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Perceiving Systems Book Chapter ElephantBook: Participatory Human–AI Elephant Population Monitoring Kulits, P., Wall, J., Beery, S. In Collaborative Intelligence: How Humans and AI Are Transforming Our World, 173-196, 7, (Editors: Lane, Mira and Sethumadhavan, Arathi), The MIT Press, Cambridge, Massachusetts, December 2024 (Published) URL BibTeX
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
Rationality Enhancement Book Chapter Life Improvement Science Lieder, F., Prentice, M. In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (Published) DOI BibTeX
Micro, Nano, and Molecular Systems Book Chapter Magnetic Micro-/Nanopropellers for Biomedicine Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P. In Field-Driven Micro and Nanorobots for Biology and Medicine, 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer, Cham, 2022 (Published) DOI URL BibTeX
Organizational Leadership and Diversity Book Chapter Stigmatization of Women in the Workplace: Sources of Stigma and its Consequences at the Individual, Organizational and Societal Level Keplinger, K., Smith, A. In Diversity in Action, 23-28, Emerald Publishing Limited, Howard House, Wagon Lane, Bingley BD16 1WA, UK, September 2022 (Published) Stigmatization of Women DOI URL 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
Robotic Materials Book Chapter Electriflow: Augmenting Books With Tangible Animation Using Soft Electrohydraulic Actuators Purnendu, , Novack, S., Acome, E., Alistar, M., Keplinger, C., Gross, M. D., Bruns, C., Leithinger, D. In ACM SIGGRAPH 2021 Labs, 1-2, Association for Computing Machinery, SIGGRAPH, August 2021 (Published) Supplemental Material DOI URL BibTeX
Embodied Vision Book Chapter TUM Flyers: Vision-Based MAV Navigation for Systematic Inspection of Structures Usenko, V., Stumberg, L. V., Stückler, J., Cremers, D. In Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users: The Experience of the European Robotics Challenges, 136:189-209, Springer Tracts in Advanced Robotics, Springer International Publishing, 2020 (Published) DOI URL BibTeX
Micro, Nano, and Molecular Systems Book Chapter Nanoscale robotic agents in biological fluids and tissues Palagi, S., Walker, D. Q. T., Fischer, P. In The Encyclopedia of Medical Robotics, 2:19-42, 2, (Editors: Desai, J. P. and Ferreira, A.), World Scientific, October 2018 (Published) DOI URL 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
Autonomous Motion Book Chapter Locally Weighted Regression for Control Ting, J., Meier, F., Vijayakumar, S., Schaal, S. In Encyclopedia of Machine Learning and Data Mining, 1-14, Springer US, Boston, MA, 2016 DOI URL 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
Physical Intelligence Book Chapter Untethered Magnetic Micromanipulation Diller, E., Sitti, M. In Micro-and Nanomanipulation Tools, 13, 10, Wiley-VCH Verlag GmbH & Co. KGaA, November 2015 DOI 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
Autonomous Motion Intelligent Control Systems Book Chapter Lernende Roboter Trimpe, S. In Jahrbuch der Max-Planck-Gesellschaft, Max Planck Society, May 2015, (popular science article in German) 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
Perceiving Systems Book Chapter Simulated Annealing Gall, J. In Encyclopedia of Computer Vision, 737-741, 0, (Editors: Ikeuchi, K. ), Springer Verlag, 2014, to appear 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