Large margin rank boundaries for ordinal regression R Herbrich, T Graepel, K Obermayer | 1470 | 2000 |

Support vector learning for ordinal regression R Herbrich, T Graepel, K Obermayer IET Digital Library, 1999 | 582 | 1999 |

Self-organizing maps: ordering, convergence properties and energy functions E Erwin, K Obermayer, K Schulten Biological cybernetics 67 (1), 47-55, 1992 | 569 | 1992 |

Geometry of orientation and ocular dominance columns in monkey striate cortex K Obermayer, GG Blasdel Journal of Neuroscience 13 (10), 4114-4129, 1993 | 419 | 1993 |

Invariant computations in local cortical networks with balanced excitation and inhibition J Mariño, J Schummers, DC Lyon, L Schwabe, O Beck, P Wiesing, ... Nature neuroscience 8 (2), 194-201, 2005 | 371 | 2005 |

Models of orientation and ocular dominance columns in the visual cortex: A critical comparison E Erwin, K Obermayer, K Schulten Neural computation 7 (3), 425-468, 1995 | 339 | 1995 |

A new summarization method for Affymetrix probe level data S Hochreiter, DA Clevert, K Obermayer Bioinformatics 22 (8), 943-949, 2006 | 334 | 2006 |

A principle for the formation of the spatial structure of cortical feature maps. K Obermayer, H Ritter, K Schulten Proceedings of the National Academy of Sciences 87 (21), 8345-8349, 1990 | 319 | 1990 |

Gaussian process regression: Active data selection and test point rejection S Seo, M Wallat, T Graepel, K Obermayer Mustererkennung 2000: 22. DAGM-Symposium. Kiel, 13.–15. September 2000, 27-34, 2000 | 294 | 2000 |

Statistical-mechanical analysis of self-organization and pattern formation during the development of visual maps K Obermayer, GG Blasdel, K Schulten Physical Review A 45 (10), 7568, 1992 | 276 | 1992 |

Soft learning vector quantization S Seo, K Obermayer Neural computation 15 (7), 1589-1604, 2003 | 273 | 2003 |

New methods for the computer-assisted 3-D reconstruction of neurons from confocal image stacks S Schmitt, JF Evers, C Duch, M Scholz, K Obermayer Neuroimage 23 (4), 1283-1298, 2004 | 246 | 2004 |

Classification on pairwise proximity data T Graepel, R Herbrich, P Bollmann-Sdorra, K Obermayer Advances in neural information processing systems 11, 1998 | 227 | 1998 |

The role of feedback in shaping the extra-classical receptive field of cortical neurons: a recurrent network model L Schwabe, K Obermayer, A Angelucci, PC Bressloff Journal of Neuroscience 26 (36), 9117-9129, 2006 | 223 | 2006 |

Self-organizing maps: Stationary states, metastability and convergence rate E Erwin, K Obermayer, K Schulten Biological Cybernetics 67, 35-45, 1992 | 201 | 1992 |

Fast model-based protein homology detection without alignment S Hochreiter, M Heusel, K Obermayer Bioinformatics 23 (14), 1728-1736, 2007 | 186 | 2007 |

Self-organizing maps: generalizations and new optimization techniques T Graepel, M Burger, K Obermayer Neurocomputing 21 (1-3), 173-190, 1998 | 179 | 1998 |

An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes F Franke, M Natora, C Boucsein, MHJ Munk, K Obermayer Journal of computational neuroscience 29, 127-148, 2010 | 168 | 2010 |

Risk-sensitive reinforcement learning Y Shen, MJ Tobia, T Sommer, K Obermayer Neural computation 26 (7), 1298-1328, 2014 | 159 | 2014 |

Quadratic optimization for simultaneous matrix diagonalization R Vollgraf, K Obermayer IEEE Transactions on Signal Processing 54 (9), 3270-3278, 2006 | 141 | 2006 |