Rojas-Carulla, M. Learning Transferable Representations University of Cambridge, UK, 2019 (phdthesis)

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Gu, S. Sample-efficient deep reinforcement learning for continuous control University of Cambridge, UK, 2019 (phdthesis)

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Ścibior*, A. Formally justified and modular Bayesian inference for probabilistic programs University of Cambridge, UK, 2019 (phdthesis)

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Xu, J. Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing Technical University of Munich, Germany, 2019 (mastersthesis)

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Weichwald, S. Pragmatism and Variable Transformations in Causal Modelling ETH Zurich, 2019 (phdthesis)

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Katiyar, P. Quantification of tumor heterogeneity using PET/MRI and machine learning Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

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Bauer, M. Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning University of Cambridge, UK, 2019 (phdthesis)

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Grimm, Dominik easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

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Sgouritsa, E. Causal Discovery Beyond Conditional Independences Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

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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)

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Muandet, K. From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

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Schuler, C. Machine Learning Approaches to Image Deconvolution University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

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Loktyushin, A. Blind Retrospective Motion Correction of MR Images University of Tübingen, Germany, May 2015 (phdthesis)

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

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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)

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Hohmann, M. A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

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Abbott, T., Abdalla, F. B., Allam, S., Amara, A., Annis, J., Armstrong, R., Bacon, D., Banerji, M., Bauer, A. H., Baxter, E., others, Cosmology from Cosmic Shear with DES Science Verification Data arXiv preprint arXiv:1507.05552, 2015 (techreport)

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Jarvis, M., Sheldon, E., Zuntz, J., Kacprzak, T., Bridle, S. L., Amara, A., Armstrong, R., Becker, M. R., Bernstein, G. M., Bonnett, C., others, The DES Science Verification Weak Lensing Shear Catalogs arXiv preprint arXiv:1507.05603, 2015 (techreport)

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Gao, M. Sequential Image Deconvolution Using Probabilistic Linear Algebra Technical University of Munich, Germany, 2015 (mastersthesis)

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Casarsa de Azevedo, L. Causal Inference in Neuroimaging Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

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Ibarra Chaoul, A. The effect of frowning on attention Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

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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)

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

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

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Shervashidze, N. Scalable graph kernels Eberhard Karls Universität Tübingen, Germany, October 2012 (phdthesis)

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Wehrl, H., Lankes, K., Hossain, M., Bezrukov, I., Liu, C., Martirosian, P., Schick, F., Pichler, B. 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)

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Wehrl, H., Lankes, K., Hossain, M., Bezrukov, I., Liu, C., Martirosian, P., Reischl, G., Schick, F., Pichler, B. 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)

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Hossain, M., Wehrl, H., Lankes, K., Liu, C., Bezrukov, I., Reischl, G., Pichler, B. Evaluation of a new, large field of view, small animal PET/MR system 50. Jahrestagung der Deutschen Gesellschaft fuer Nuklearmedizin (NuklearMedizin), April 2012 (talk)

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Kober, J. Learning Motor Skills: From Algorithms to Robot Experiments Technische Universität Darmstadt, Germany, March 2012 (phdthesis)

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Grosse-Wentrup, M., Schölkopf, B. High Gamma-Power Predicts Performance in Brain-Computer Interfacing (3), Max-Planck-Institut für Intelligente Systeme, Tübingen, February 2012 (techreport)

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Wehrl, H., Hossain, M., Lankes, K., Liu, C., Bezrukov, I., Martirosian, P., Reischl, G., Schick, F., Pichler, B. Simultaneous small animal PET/MR reveals different brain networks during stimulation and rest World Molecular Imaging Congress (WMIC), 2012 (talk)

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

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

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Liu, C., Hossain, M., Lankes, K., Bezrukov, I., Wehrl, H., Kolb, A., Judenhofer, M., Pichler, B. PET Performance Measurements of a Next Generation Dedicated Small Animal PET/MR Scanner Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), 2012 (talk)

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Gomez Rodriguez, M. Structure and Dynamics of Diffusion Networks Department of Electrical Engineering, Stanford University, 2012 (phdthesis)

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Hirsch, M. Blind Deconvolution in Scientific Imaging & Computational Photography Eberhard Karls Universität Tübingen, Germany, 2012 (phdthesis)

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Seldin, Y., Laviolette, F., Shawe-Taylor, J. PAC-Bayesian Analysis of Supervised, Unsupervised, and Reinforcement Learning Tutorial at the 29th International Conference on Machine Learning (ICML), 2012 (talk)

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Bezrukov, I., Schmidt, H., Mantlik, F., Schwenzer, N., Brendle, C., Pichler, B. Influence of MR-based attenuation correction on lesions within bone and susceptibility artifact regions Molekulare Bildgebung (MoBi), 2012 (talk)

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Peters, J. Restricted structural equation models for causal inference ETH Zurich, Switzerland, 2012 (phdthesis)

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Boularias, A., Kroemer, O., Peters, J. Structured Apprenticeship Learning European Workshop on Reinforcement Learning (EWRL), 2012 (talk)

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Seldin, Y., Laviolette, F., Shawe-Taylor, J. 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)

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

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Nishiyama, Y., Boularias, A., Gretton, A., Fukumizu, K. Kernel Bellman Equations in POMDPs Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML'12), 2012 (talk)

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Panagiotaropoulos, T., Besserve, M., Logothetis, N. Beta oscillations propagate as traveling waves in the macaque prefrontal cortex 42nd Annual Meeting of the Society for Neuroscience (Neuroscience), 2012 (talk)

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Jegelka, S. Combinatorial Problems with Submodular Coupling in Machine Learning and Computer Vision ETH Zürich, Switzerland, 2012 (phdthesis)

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Hooge, J. Automatische Seitenkettenzuordnung zur NMR Proteinstrukturaufklärung mittels ganzzahliger linearer Programmierung University of Tübingen, Germany, 2012 (diplomathesis)

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Klenske, E. D. Nonparametric System Identification and Control for Periodic Error Correction in Telescopes University of Stuttgart, 2012 (diplomathesis)

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Chapelle, O. Some thoughts about Gaussian Processes NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

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Chapelle, O. A taxonomy of semi-supervised learning algorithms Yahoo!, December 2005 (talk)

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Corfield, D., Schölkopf, B., Vapnik, V. Popper, Falsification and the VC-dimension (145), Max Planck Institute for Biological Cybernetics, November 2005 (techreport)

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