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Journal Article (17)

  1. 1.
    Journal Article
    Kim, J.; Müller, K.-R.; Chung, Y.; Chung, S.-C.; Park, J.-Y.; Bülthoff, H.; Kim, S.-P.: Distributed functions of detection and discrimination of vibrotactile stimuli in the hierarchical human somatosensory system. Frontiers in Human Neuroscience 8 (2015)
  2. 2.
    Journal Article
    Biessmann, F.; Murayama, Y.; Logothetis, N.; Müller, K.; Meinecke, F.: Improved decoding of neural activity from fMRI signals using non-separable spatiotemporal deconvolutions. NeuroImage 61 (4), pp. 1031 - 1042 (2012)
  3. 3.
    Journal Article
    Murayama, Y.; Biessmann, F.; Meinecke, F.; Müller, K.-R.; Augath, M.; Oeltermann, A.; Logothetis, N.: Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA. Magnetic Resonance Imaging 28 (8), pp. 1095 - 1103 (2010)
  4. 4.
    Journal Article
    Baehrens, D.; Schroeter, T.; Harmeling, S.; Kawanabe, M.; Hansen, K.; Müller, K.-R.: How to Explain Individual Classification Decisions. Journal of Machine Learning Research 11, pp. 1803 - 1831 (2010)
  5. 5.
    Journal Article
    Biessmann, F.; Meinecke, F.; Gretton, A.; Rauch, A.; Rainer, G.; Logothetis, N.; Müller, K.-R.: Temporal Kernel CCA and its Application in Multimodal Neuronal Data Analysis. Machine Learning 79 (1-2), pp. 5 - 27 (2010)
  6. 6.
    Journal Article
    Sonnenburg, S.; Braun, M.; Ong, C.; Bengio, S.; Bottou, L.; Holmes , G.; LeCun, Y.; Müller, K.-R.; Pereira, F.; Rasmussen, C. et al.; Rätsch, G.; Schölkopf, B.; Smola, A.; Vincent, P.; Weston, J.; Williamson, R.: The Need for Open Source Software in Machine Learning. The Journal of Machine Learning Research 8, pp. 2443 - 2466 (2007)
  7. 7.
    Journal Article
    Rätsch, G.; Sonnenburg, S.; Srinivasan, J.; Witte, H.; Müller, K.-R.; Sommer, R.-J.; Schölkopf, B.: Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning. PLoS Computational Biology 3 (2 ), pp. 0313 - 0322 (2007)
  8. 8.
    Journal Article
    Harmeling, S.; Dornhege, G.; Tax, D.; Meinecke, F.; Müller, K.-R.: From outliers to prototypes: Ordering data. Neurocomputing 69 (13-15), pp. 1608 - 1618 (2006)
  9. 9.
    Journal Article
    Meinecke, F.; Harmeling, S.; Müller, K.-R.: Inlier-based ICA with an application to superimposed images. International Journal of Imaging Systems and Technology 15 (1), pp. 48 - 55 (2005)
  10. 10.
    Journal Article
    Harmeling, S.; Meinecke, F.; Müller, K.-R.: Injecting noise for analysing the stability of ICA components. Signal Processing 84 (2), pp. 255 - 266 (2004)
  11. 11.
    Journal Article
    Ziehe, A.; Kawanabe M, Harmeling, S.; Müller, K.-R.: Blind separation of post-nonlinear mixtures using linearizing transformations and temporal decorrelation. Journal of Machine Learning Research 4 (7-8), pp. 1319 - 1338 (2003)
  12. 12.
    Journal Article
    Harmeling, S.; Ziehe A, Kawanabe, M.; Müller, K.-R.: Kernel-based nonlinear blind source separation. Neural Computation 15 (5), pp. 1089 - 1124 (2003)
  13. 13.
    Journal Article
    Mika, S.; Rätsch, G.; Weston, J.; Schölkopf, B.; Smola, A.; Müller, K.-R.: Constructing Descriptive and Discriminative Non-linear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (5), pp. 623 - 628 (2003)
  14. 14.
    Journal Article
    Rätsch, G.; Mika S, Schölkopf, B.; Müller, K.-R.: Constructing Boosting algorithms from SVMs: an application to one-class classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (9), pp. 1184 - 1199 (2002)
  15. 15.
    Journal Article
    Müller, K.-R.; Mika S, Rätsch, G.; Tsuda, K.; Schölkopf, B.: An Introduction to Kernel-Based Learning Algorithms. IEEE Transactions on Neural Networks 12 (2), pp. 181 - 201 (2001)
  16. 16.
    Journal Article
    Zien, A.; Rätsch, G.; Mika S, Schölkopf, B.; Lengauer, T.; Müller, K.-R.: Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites. Bioinformatics 16 (9), pp. 799 - 807 (2000)
  17. 17.
    Journal Article
    Smola, A.; Schölkopf, B.; Müller, K.-R.: The connection between regularization operators and support vector kernels. Neural Networks 11 (4), pp. 637 - 649 (1998)

Book (1)

  1. 18.
    Book
    Lee, S.-W.; Bülthoff, H.; Müller, K.-R. (Eds.): Recent Progress in Brain and Cognitive Engineering. Springer, Dordrecht, The Netherlands (2015), 213 pp.

Book Chapter (1)

  1. 19.
    Book Chapter
    Rätsch, G.; Schölkopf, B.; Smola AJ, Mika S, Onoda, T.; Müller, K.-R.: Robust ensemble learning. In: Advances in Large Margin Classifiers, pp. 207 - 220. MIT Press, Cambridge, MA, USA (2000)

Conference Paper (10)

  1. 20.
    Conference Paper
    Biessmann, F.; Murayama, Y.; Logothetis, N.; Müller, K.-R.; Meinecke, F.: Non-separable Spatiotemporal Brain Hemodynamics Contain Neural Information. In: Machine Learning and Interpretation in Neuroimaging, pp. 140 - 147 (Eds. Langs, G.; Rish, I.; Murphy, B.). NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI 2011), Sierra Nevada, Spain, December 16, 2011 - December 17, 2011. Springer, Berlin, Germany (2012)
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