ei Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G. Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller Journal of Intelligent & Robotic Systems, 83(3-4):393-408, (Editors: Luis Almeida, Lino Marques ), September 2016, Special Issue: Autonomous Robot Systems (article)

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ei Maeda, G., Ewerton, M., Koert, D., Peters, J. Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)

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ei Zhang, K., Wang, Z., Zhang, J., Schölkopf, B. On estimation of functional causal models: General results and application to post-nonlinear causal model ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)

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ei pn Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P. Gaussian Process-Based Predictive Control for Periodic Error Correction IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)

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ei Townsend, J., Koep, N., Weichwald, S. Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation Journal of Machine Learning Research, 17(137):1-5, 2016 (article)

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ei Wang, D., Hogg, D. W., Foreman-Mackey, D., Schölkopf, B. A Causal, Data-driven Approach to Modeling the Kepler Data Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)

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am ei Daniel, C., van Hoof, H., Peters, J., Neumann, G. Probabilistic Inference for Determining Options in Reinforcement Learning Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)

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ei Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R. Influence of initial fixation position in scene viewing Vision Research, 129, pages: 33-49, 2016 (article)

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ei Wallis, T. S. A., Bethge, M., Wichmann, F. A. Testing models of peripheral encoding using metamerism in an oddity paradigm Journal of Vision, 16(2), 2016 (article)

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ei Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J. Modeling Confounding by Half-Sibling Regression Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)

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ei pn Klenske, E. D., Hennig, P. Dual Control for Approximate Bayesian Reinforcement Learning Journal of Machine Learning Research, 17(127):1-30, 2016 (article)

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ei Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J. A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)

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ei Seith, F., Gatidis, S., Schmidt, H., Bezrukov, I., la Fougère, C., Nikolaou, K., Pfannenberg, C., Schwenzer, N. Comparison of Positron Emission Tomography Quantification Using Magnetic Resonance–and Computed Tomography–Based Attenuation Correction in Physiological Tissues and Lesions: A Whole-Body Positron Emission Tomography/Magnetic Resonance Study in 66 Patients Investigative Radiology, 51(1):66-71, 2016 (article)

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ei Gomez Rodriguez, M., Song, L., Daneshmand, H., Schölkopf, B. Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm Journal of Machine Learning Research, 17(90):1-29, 2016 (article)

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ei Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A. Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data Vision Research, 122, pages: 105-123, 2016 (article)

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ei Grosse-Wentrup, M., Janzing, D., Siegel, M., Schölkopf, B. Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach NeuroImage, 125, pages: 825-833, 2016 (article)

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ei Köhler, R. Advances in computational imaging: Benchmarking Deblurring Algorithms, Deep Neural Inpainting, Depth Estimation from Light Fields Eberhard Karls Universität Tübingen, Germany, 2016 (phdthesis)

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ei Daniel, C., Neumann, G., Kroemer, O., Peters, J. Hierarchical Relative Entropy Policy Search Journal of Machine Learning Research, 17(93):1-50, 2016 (article)

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ei Kiefel, M. Tractable Structured Prediction using the Permutohedral Lattice ETH Zurich, 2016 (phdthesis)

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ei Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B. Kernel Mean Shrinkage Estimators Journal of Machine Learning Research, 17(48):1-41, 2016 (article)

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ei Schuler, C. J., Hirsch, M., Harmeling, S., Schölkopf, B. Learning to Deblur IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7):1439-1451, IEEE, 2016 (article)

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ei Jayaram, V., Alamgir, M., Altun, Y., Schölkopf, B., Grosse-Wentrup, M. Transfer Learning in Brain-Computer Interfaces IEEE Computational Intelligence Magazine, 11(1):20-31, 2016 (article)

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ei Weichwald, S., Grosse-Wentrup, M., Gretton, A. MERLiN: Mixture Effect Recovery in Linear Networks IEEE Journal of Selected Topics in Signal Processing, 10(7):1254-1266, 2016 (article)

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ei Peters, J., Bühlmann, P., Meinshausen, N. Causal inference using invariant prediction: identification and confidence intervals Journal of the Royal Statistical Society, Series B (Statistical Methodology), 78(5):947-1012, 2016, (with discussion) (article)

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ei Spirtes, P., Zhang, K. Causal discovery and inference: concepts and recent methodological advances Applied Informatics, 3(3):1-28, 2016 (article)

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ei Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M. Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS Journal of Neural Engineering, 13(6):066021, 2016 (article)

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ei Gomez-Rodriguez, M., Song, L., Du, N., Zha, H., Schölkopf, B. Influence Estimation and Maximization in Continuous-Time Diffusion Networks ACM Transactions on Information Systems, 34(2):9:1-9:33, 2016 (article)

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ei Stimper, V. Zwischen Harmonie und Chaos - ein verallgemeinertes Modell des Doppelpendels Junge Wissenschaft, (109), 2016 (article)

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ei Foreman-Mackey, D., Morton, T. D., Hogg, D. W., Agol, E., Schölkopf, B. The population of long-period transiting exoplanets The Astronomical Journal, 152(6):206, 2016 (article)

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ei Jäkel, F., Singh, M., Wichmann, F. A., Herzog, M. H. An overview of quantitative approaches in Gestalt perception Vision Research, 126, pages: 3-8, 2016 (article)

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ei Huang, H., Peloso, G. M., Howrigan, D., Rakitsch, B., Simon-Gabriel, C. J., Goldstein, J. I., Daly, M. J., Borgwardt, K., Neale, B. M. Bootstrat: Population Informed Bootstrapping for Rare Variant Tests bioRxiv, 2016, preprint (article)

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ei Rueckert, E., Camernik, J., Peters, J., Babic, J. Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control Nature PG: Scientific Reports, 6(Article number: 28455), 2016 (article)

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ei Mooij, J., Peters, J., Janzing, D., Zscheischler, J., Schölkopf, B. Distinguishing cause from effect using observational data: methods and benchmarks Journal of Machine Learning Research, 17(32):1-102, 2016 (article)

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ei Babbar, R., Partalas, I., Gaussier, E., Amini, M., Amblard, C. Learning Taxonomy Adaptation in Large-scale Classification Journal of Machine Learning Research, 17(98):1-37, 2016 (article)

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ei Janzing, D., Chaves, R., Schölkopf, B. Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference New Journal of Phyiscs, 18(9):093052, 2016 (article)

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ei Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A., Obermayer, K. BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors Frontiers in Psychology, 2016 (article)

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ei Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J. Preface to the ACM TIST Special Issue on Causal Discovery and Inference ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 17, 2016 (article)

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ei Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., Peters, J. Recurrent Spiking Networks Solve Planning Tasks Nature PG: Scientific Reports, 6(Article number: 21142), 2016 (article)

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ei Genewein, T, Braun, DA Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations Biological Cybernetics, 110(2):135–150, June 2016 (article)

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ei Grau-Moya, J, Ortega, PA, Braun, DA Decision-Making under Ambiguity Is Modulated by Visual Framing, but Not by Motor vs. Non-Motor Context: Experiments and an Information-Theoretic Ambiguity Model PLoS ONE, 11(4):1-21, April 2016 (article)

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ei Gretton, A., Herbrich, R., Smola, A., Bousquet, O., Schölkopf, B. Kernel Methods for Measuring Independence Journal of Machine Learning Research, 6, pages: 2075-2129, December 2005 (article)

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ei Quinonero Candela, J., Rasmussen, C. A Unifying View of Sparse Approximate Gaussian Process Regression Journal of Machine Learning Research, 6, pages: 1935-1959, December 2005 (article)

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ei BakIr, G. Extension to Kernel Dependency Estimation with Applications to Robotics Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

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ei Hein, M. Geometrical aspects of statistical learning theory Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

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ei Hein, M., Bousquet, O., Schölkopf, B. Maximal Margin Classification for Metric Spaces Journal of Computer and System Sciences, 71(3):333-359, October 2005 (article)

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ei Kato, T., Tsuda, K., Asai, K. Selective integration of multiple biological data for supervised network inference Bioinformatics, 21(10):2488 , October 2005 (article)

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ei Kuss, M., Rasmussen, C. Assessing Approximate Inference for Binary Gaussian Process Classification Journal of Machine Learning Research, 6, pages: 1679 , October 2005 (article)

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ei Steinke, F. Implicit Surfaces For Modelling Human Heads Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

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ei Banerjee, A., Dhillon, I., Ghosh, J., Sra, S. Clustering on the Unit Hypersphere using von Mises-Fisher Distributions Journal of Machine Learning Research, 6, pages: 1345-1382, September 2005 (article)

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ei Steinke, F., Schölkopf, B., Blanz, V. Support Vector Machines for 3D Shape Processing Computer Graphics Forum, 24(3, EUROGRAPHICS 2005):285-294, September 2005 (article)

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