Critical assessment of automated flow cytometry data analysis techniques N Aghaeepour, G Finak, FlowCAP Consortium, Dream Consortium, ... Nature methods 10 (3), 228-238, 2013 | 679 | 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 | 153 | 2012 |
A general framework for dimensionality-reducing data visualization mapping K Bunte, M Biehl, B Hammer Neural Computation 24 (3), 771-804, 2012 | 136 | 2012 |
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 | 126 | 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 | 115 | 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 | 98 | 2011 |
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), 12460, 2016 | 94 | 2016 |
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 | 80 | 2010 |
Exploratory observation machine (XOM) with Kullback-Leibler divergence for dimensionality reduction and visualization K Bunte, B Hammer, T Villmann, M Biehl, A Wismüller 18th European Symposium on Artificial Neural Networks (ESANN 2010), 87-92, 2010 | 77 | 2010 |
Neighbor embedding XOM for dimension reduction and visualization K Bunte, B Hammer, T Villmann, M Biehl, A Wismüller Neurocomputing 74 (9), 1340-1350, 2011 | 74 | 2011 |
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 | 65 | 2012 |
Analysis of flow cytometry data by matrix relevance learning vector quantization M Biehl, K Bunte, P Schneider PLoS One 8 (3), e59401, 2013 | 58 | 2013 |
Sparse group factor analysis for biclustering of multiple data sources K Bunte, E Leppäaho, I Saarinen, S Kaski Bioinformatics 32 (16), 2457-2463, 2016 | 52 | 2016 |
Waypoint averaging and step size control in learning by gradient descent G Papari, K Bunte, M Biehl Machine Learning Reports 6, 16, 2011 | 31 | 2011 |
Positive and negative parenting in conduct disorder with high versus low levels of callous–unemotional traits R Pauli, P Tino, JC Rogers, R Baker, R Clanton, P Birch, A Brown, ... Development and psychopathology 33 (3), 980-991, 2021 | 29 | 2021 |
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 | 28 | 2012 |
A community challenge for inferring genetic predictors of gene essentialities through analysis of a functional screen of cancer cell lines M Gönen, BA Weir, GS Cowley, F Vazquez, Y Guan, A Jaiswal, ... Cell systems 5 (5), 485-497. e3, 2017 | 24 | 2017 |
Optimal neighborhood preserving visualization by maximum satisfiability K Bunte, M Järvisalo, J Berg, P Myllymäki, J Peltonen, S Kaski Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 23 | 2014 |
Learning pharmacokinetic models for in vivo glucocorticoid activation K Bunte, DJ Smith, MJ Chappell, ZK Hassan-Smith, JW Tomlinson, W Arlt, ... Journal of Theoretical Biology 455, 222-231, 2018 | 21 | 2018 |
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 | 21 | 2008 |