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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)
Maeda, G., Maloo, A., Ewerton, M., Lioutikov, R., Peters, J.
Proactive Human-Robot Collaboration with Interaction Primitives
9th International Workshop on Human-Friendly Robotics (HFR), pages: 40-45, 2016 (conference)
ei
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)
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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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Perceiving Systems (2011-2015)
Scientific Advisory Board Report, 2016 (misc)
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Yeo, S. Y., Romero, J., Loper, M., Machann, J., Black, M.
Shape estimation of subcutaneous adipose tissue using an articulated statistical shape model
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 0(0):1-8, 2016 (article)
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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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Anderson, M., Anderson, S. L., Berenz, V.
Ensuring Ethical Behavior from Autonomous Systems
In Artificial Intelligence Applied to Assistive Technologies and Smart Environments, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016, 2016 (inproceedings)
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Mescheder, L., Nowozin, S., Geiger, A.
Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring
Arxiv, 2016 (article)
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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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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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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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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)
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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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Kiefel, M.
Tractable Structured Prediction using the Permutohedral Lattice
ETH Zurich, 2016 (phdthesis)
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Puidokait, M., Graefe, J., Sehl, A., Steinke, K., Siehl, H., Zeller, K., Sicker, D., Berger, S.
γ‐Conicein und Coniin aus Geflecktem Schierling
Chemie in unserer Zeit, 50(6):382-391, 2016 (article)
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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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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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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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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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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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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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Meier, F., Kappler, D., Ratliff, N., Schaal, S.
Towards Robust Online Inverse Dynamics Learning
Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, IEEE, IROS, 2016 (conference) Accepted
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Chebotar, Y., Hausman, K., Su, Z., Sukhatme, G., Schaal, S.
Self-Supervised Regrasping using Spatio-Temporal Tactile Features and Reinforcement Learning
In International Conference on Intelligent Robots and Systems (IROS) 2016, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016 (inproceedings)
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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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Jeong, H. H., Lee, T. C., Fischer, P.
Method for encapsulating a nanostructure, coated nanostructure and use of a coated nanostructure
Google Patents, 2016, WO Patent App. PCT/EP2016/056,377 (patent)
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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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Büchler, D., Calandra, R., Peters, J.
Modeling Variability of Musculoskeletal Systems with Heteroscedastic Gaussian Processes
Workshop on Neurorobotics, Neural Information Processing Systems (NIPS), 2016 (conference)
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Tzionas, D., Gall, J.
Reconstructing Articulated Rigged Models from RGB-D Videos
In European Conference on Computer Vision Workshops 2016 (ECCVW’16) - Workshop on Recovering 6D Object Pose (R6D’16), pages: 620-633, Springer International Publishing, 2016 (inproceedings)
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Ting, J., Meier, F., Vijayakumar, S., Schaal, S.
Locally Weighted Regression for Control
In Encyclopedia of Machine Learning and Data Mining, pages: 1-14, Springer US, Boston, MA, 2016 (inbook)
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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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Laidig, D., Trimpe, S., Seel, T.
Event-based Sampling for Reducing Communication Load in Realtime Human Motion Analysis by Wireless Inertial Sensor Networks
Current Directions in Biomedical Engineering, 2(1):711-714, De Gruyter, 2016 (article)
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Chebotar, Y., Hausman, K., Kroemer, O., Sukhatme, G., Schaal, S.
Generalizing Regrasping with Supervised Policy Learning
In International Symposium on Experimental Robotics (ISER) 2016, International Symposium on Experimental Robotics, 2016 (inproceedings)
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Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.
Statistical source separation of rhythmic LFP patterns during sharp wave ripples in the macaque hippocampus
47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)
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Raj, A., Olbrich, J., Gärtner, B., Schölkopf, B., Jaggi, M.
Screening Rules for Convex Problems
2016 (unpublished) Submitted
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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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Schölkopf, B., Janzing, D., Lopez-Paz, D.
Causal and statistical learning
Oberwolfach Reports, 13(3):1896-1899, (Editors: A. Christmann and K. Jetter and S. Smale and D.-X. Zhou), 2016 (conference)
Mittemeijer, Eric J.; Wang, Zumin
Interface-controlled phenomena in nanomaterials
2016 (mpi_year_book)
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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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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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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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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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Feix, T., Romero, J., Schmiedmayer, H., Dollar, A., Kragic, D.
The GRASP Taxonomy of Human Grasp Types
Human-Machine Systems, IEEE Transactions on, 46(1):66-77, 2016 (article)
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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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Besserve, M., Logothetis, N. K.
Hippocampal neural events predict ongoing brain-wide BOLD activity
47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)
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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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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)
Geiger, A.
Robots learn how to see
2016 (mpi_year_book)
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Brubaker, M. A., Geiger, A., Urtasun, R.
Map-Based Probabilistic Visual Self-Localization
IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)