Critical assessment of automated flow cytometry data analysis techniques N Aghaeepour, G Finak, H Hoos, TR Mosmann, R Brinkman, R Gottardo, ... Nature methods 10 (3), 228, 2013 | 435 | 2013 |

Limited rank matrix learning, discriminative dimension reduction and visualization K Bunte, P Schneider, B Hammer, FM Schleif, T Villmann, M Biehl Neural Networks 26, 159-173, 2012 | 100 | 2012 |

Regularization in matrix relevance learning P Schneider, K Bunte, H Stiekema, B Hammer, T Villmann, M Biehl IEEE Transactions on Neural Networks 21 (5), 831-840, 2010 | 91 | 2010 |

Learning effective color features for content based image retrieval in dermatology K Bunte, M Biehl, MF Jonkman, N Petkov Pattern Recognition 44 (9), 1892-1902, 2011 | 79 | 2011 |

A general framework for dimensionality-reducing data visualization mapping K Bunte, M Biehl, B Hammer Neural Computation 24 (3), 771-804, 2012 | 68 | 2012 |

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis SK Sieberts, F Zhu, J García-García, E Stahl, A Pratap, G Pandey, ... Nature communications 7 (1), 1-10, 2016 | 60 | 2016 |

Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences K Bunte, S Haase, M Biehl, T Villmann Neurocomputing 90, 23-45, 2012 | 52 | 2012 |

Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data K Bunte, B Hammer, A Wismüller, M Biehl Neurocomputing 73 (7-9), 1074-1092, 2010 | 48 | 2010 |

Analysis of flow cytometry data by matrix relevance learning vector quantization M Biehl, K Bunte, P Schneider PLoS One 8 (3), 2013 | 42 | 2013 |

Neighbor embedding XOM for dimension reduction and visualization K Bunte, B Hammer, T Villmann, M Biehl, A Wismüller Neurocomputing 74 (9), 1340-1350, 2011 | 42 | 2011 |

Exploratory observation machine (xom) with kullback-leibler divergence for dimensionality reduction and visualization. K Bunte, B Hammer, T Villmann, M Biehl, A Wismüller ESANN 10, 87-92, 2010 | 41 | 2010 |

Sparse group factor analysis for biclustering of multiple data sources K Bunte, E Leppäaho, I Saarinen, S Kaski Bioinformatics 32 (16), 2457-2463, 2016 | 29 | 2016 |

Texture feature ranking with relevance learning to classify interstitial lung disease patterns MB Huber, K Bunte, MB Nagarajan, M Biehl, LA Ray, A Wismüller Artificial intelligence in medicine 56 (2), 91-97, 2012 | 29 | 2012 |

Large margin linear discriminative visualization by matrix relevance learning M Biehl, K Bunte, FM Schleif, P Schneider, T Villmann The 2012 International Joint Conference on Neural Networks (IJCNN), 1-8, 2012 | 20 | 2012 |

Discriminative visualization by limited rank matrix learning K Bunte, P Schneider, B Hammer, FM Schleif, T Villmann, M Biehl Machine Learning Reports 2, 37-51, 2008 | 20 | 2008 |

Optimal neighborhood preserving visualization by maximum satisfiability K Bunte, M Järvisalo, J Berg, P Myllymäki, J Peltonen, S Kaski Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014 | 18 | 2014 |

Waypoint averaging and step size control in learning by gradient descent G Papari, K Bunte, M Biehl Machine Learning Reports 6, 16, 2011 | 18 | 2011 |

Adaptive matrices and filters for color texture classification I Giotis, K Bunte, N Petkov, M Biehl Journal of Mathematical Imaging and Vision 47 (1-2), 79-92, 2013 | 14 | 2013 |

Dimensionality reduction mappings K Bunte, M Biehl, B Hammer 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM …, 2011 | 14 | 2011 |

Neurocomputing. 9. Vol. 74 K Bunte, B Hammer, T Villmann, M Biehl, A Wismüller Elsevier, 2011 | 13 | 2011 |