Thomas Villmann

	2012
129		Marika Kästner, Thomas Villmann: Fuzzy Supervised Self-Organizing Map for Semi-supervised Vector Quantization. ICAISC (1) 2012: 256-265
128		Thomas Villmann, Tina Geweniger, Marika Kästner, Mandy Lange: Fuzzy Neural Gas for Unsupervised Vector Quantization. ICAISC (1) 2012: 350-358
127		Kerstin Bunte, Petra Schneider, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann, Michael Biehl: Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks 26: 159-173 (2012)
	2011
126		Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann: Generalized functional relevance learning vector quantization. ESANN 2011
125		Thomas Villmann, José C. Príncipe, Andrzej Cichocki: Information theory related learning. ESANN 2011
124		Kerstin Bunte, Frank-Michael Schleif, Sven Haase, Thomas Villmann: Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. ESANN 2011
123		Marc Strickert, Björn Labitzke, Andreas Kolb, Thomas Villmann: Multispectral image characterization by partial generalized covariance. ESANN 2011
122		Petra Schneider, Tina Geweniger, Frank-Michael Schleif, Michael Biehl, Thomas Villmann: Multivariate class labeling in Robust Soft LVQ. ESANN 2011
121		Tina Geweniger, Marika Kästner, Thomas Villmann: Optimization of Parametrized Divergences in Fuzzy c-Means. ESANN 2011
120		Thomas Villmann, Sven Haase: Magnification in divergence based neural maps. IJCNN 2011: 437-441
119		Thomas Villmann, Marika Kästner: Sparse Functional Relevance Learning in Generalized Learning Vector Quantization. WSOM 2011: 79-89
118		Marika Kästner, Andreas Backhaus, Tina Geweniger, Sven Haase, Udo Seiffert, Thomas Villmann: Relevance Learning in Unsupervised Vector Quantization Based on Divergences. WSOM 2011: 90-100
117		Michael Biehl, Barbara Hammer, Erzsébet Merényi, Alessandro Sperduti, Thomas Villmann: Learning in the context of very high dimensional data (Dagstuhl Seminar 11341). Dagstuhl Reports 1(8): 67-95 (2011)
116		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Petra Schneider: Efficient Kernelized Prototype Based Classification. Int. J. Neural Syst. 21(6): 443-457 (2011)
115		Thomas Villmann, Sven Haase: Divergence-Based Vector Quantization. Neural Computation 23(5): 1343-1392 (2011)
114		Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller: Neighbor embedding XOM for dimension reduction and visualization. Neurocomputing 74(9): 1340-1350 (2011)
113		Ernest Mwebaze, Petra Schneider, Frank-Michael Schleif, Jennifer R. Aduwo, John A. Quinn, Sven Haase, Thomas Villmann, Michael Biehl: Divergence-based classification in learning vector quantization. Neurocomputing 74(9): 1429-1435 (2011)
	2010
112		Thomas Villmann, Sven Haase, Frank-Michael Schleif, Barbara Hammer, Michael Biehl: The Mathematics of Divergence Based Online Learning in Vector Quantization. ANNPR 2010: 108-119
111		Andreas Schierwagen, Thomas Villmann, Alán Alpár, Ulrich Gärtner: Cluster Analysis of Cortical Pyramidal Neurons Using SOM. ANNPR 2010: 120-130
110		Ernest Mwebaze, Petra Schneider, Frank-Michael Schleif, Sven Haase, Thomas Villmann, Michael Biehl: Divergence based Learning Vector Quantization. ESANN 2010
109		Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller: Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization. ESANN 2010
108		Tina Geweniger, Thomas Villmann: Extending FSNPC to handle data points with fuzzy class assignments. ESANN 2010
107		Dietlind Zühlke, Frank-Michael Schleif, Tina Geweniger, Sven Haase, Thomas Villmann: Learning vector quantization for heterogeneous structured data. ESANN 2010
106		Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Sparse representation of data. ESANN 2010
105		Thomas Villmann, Sven Haase, Frank-Michael Schleif, Barbara Hammer: Divergence Based Online Learning in Vector Quantization. ICAISC (1) 2010: 479-486
104		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Petra Schneider, Michael Biehl: Generalized Derivative Based Kernelized Learning Vector Quantization. IDEAL 2010: 21-28
103		Petra Schneider, Kerstin Bunte, Han Stiekema, Barbara Hammer, Thomas Villmann, Michael Biehl: Regularization in matrix relevance learning. IEEE Transactions on Neural Networks 21(5): 831-840 (2010)
102		Stephan Simmuteit, Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints. Knowl. Inf. Syst. 25(2): 327-343 (2010)
101		Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Median fuzzy c-means for clustering dissimilarity data. Neurocomputing 73(7-9): 1109-1116 (2010)
	2009
100		Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann: Similarity-Based Clustering, Recent Developments and Biomedical Applications [outcome of a Dagstuhl Seminar] Springer 2009
99		Dietlind Zühlke, Tina Geweniger, Ulrich Heimann, Thomas Villmann: Fuzzy Fleiss-kappa for Comparison of Fuzzy Classifiers. ESANN 2009
98		Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Median Variant of Fuzzy c-Means. ESANN 2009
97		Frank-Michael Schleif, Thomas Villmann: Neural Maps and Learning Vector Quantization - Theory and Applications. ESANN 2009
96		Stephan Simmuteit, Frank-Michael Schleif, Thomas Villmann, Thomas Elssner: Tanimoto Metric in Tree-SOM for Improved Representation of Mass Spectrometry Data with an Underlying Taxonomic Structure. ICMLA 2009: 563-567
95		Marc Strickert, Jens Keilwagen, Frank-Michael Schleif, Thomas Villmann, Michael Biehl: Matrix Metric Adaptation Linear Discriminant Analysis of Biomedical Data. IWANN (1) 2009: 933-940
94		Thomas Villmann, Barbara Hammer, Michael Biehl: Some Theoretical Aspects of the Neural Gas Vector Quantizer. Similarity-Based Clustering 2009: 23-34
93		Marc Strickert, Frank-Michael Schleif, Thomas Villmann, Udo Seiffert: Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. Similarity-Based Clustering 2009: 70-91
92		Stephan Simmuteit, Frank-Michael Schleif, Thomas Villmann, Markus Kostrzewa: Hierarchical PCA Using Tree-SOM for the Identification of Bacteria. WSOM 2009: 272-280
91		Thomas Villmann, Barbara Hammer: Functional Principal Component Learning Using Oja's Method and Sobolev Norms. WSOM 2009: 325-333
90		Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means. WSOM 2009: 72-79
89		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Prototype Based Classification in Bioinformatics. Encyclopedia of Artificial Intelligence 2009: 1337-1342
88		Michael Biehl, Barbara Hammer, Petra Schneider, Thomas Villmann: Metric Learning for Prototype-Based Classification. Innovations in Neural Information Paradigms and Applications 2009: 183-199
87		Frank-Michael Schleif, Thomas Villmann, Markus Kostrzewa, Barbara Hammer, Alexander Gammerman: Cancer informatics by prototype networks in mass spectrometry. Artificial Intelligence in Medicine 45(2-3): 215-228 (2009)
86		Frank-Michael Schleif, Thomas Villmann, Matthias Ongyerth: Supervised data analysis and reliability estimation with exemplary application for spectral data. Neurocomputing 72(16-18): 3590-3601 (2009)
	2008
85		Marc Strickert, Petra Schneider, Jens Keilwagen, Thomas Villmann, Michael Biehl, Barbara Hammer: Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics. ANNPR 2008: 78-89
84		Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer: Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203
83		Frank-Michael Schleif, Matthias Ongyerth, Thomas Villmann: Sparse Coding Neural Gas for Analysis of Nuclear Magnetic Resonance Spectroscopy. CBMS 2008: 620-625
82		Marc Strickert, Frank-Michael Schleif, Thomas Villmann: Metric adaptation for supervised attribute rating. ESANN 2008: 31-36
81		Alexander Hasenfuss, Barbara Hammer, Tina Geweniger, Thomas Villmann: Magnification Control in Relational Neural Gas. ESANN 2008: 325-330
80		Thomas Villmann, Erzsébet Merényi, Udo Seiffert: Machine learning approches and pattern recognition for spectral data. ESANN 2008: 433-444
79		Petra Schneider, Frank-Michael Schleif, Thomas Villmann, Michael Biehl: Generalized matrix learning vector quantizer for the analysis of spectral data. ESANN 2008: 451-456
78		Tina Geweniger, Frank-Michael Schleif, Alexander Hasenfuss, Barbara Hammer, Thomas Villmann: Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity. ICONIP (2) 2008: 61-69
77		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Martijn van der Werff, André M. Deelder, Rob A. E. M. Tollenaar: Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers. Computational Intelligence in Biomedicine and Bioinformatics 2008: 141-167
76		Thomas Villmann, Frank-Michael Schleif, Markus Kostrzewa, Axel Walch, Barbara Hammer: Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics 9(2): 129-143 (2008)
75		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Prototype based fuzzy classification in clinical proteomics. Int. J. Approx. Reasoning 47(1): 4-16 (2008)
74		Marc Strickert, Frank-Michael Schleif, Udo Seiffert, Thomas Villmann: Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 12(37): 37-44 (2008)
	2007
73		Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann: Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007 Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2007
72		Thomas Villmann, Marc Strickert, Cornelia Brüß, Frank-Michael Schleif, Udo Seiffert: Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. ESANN 2007: 103-108
71		Barbara Hammer, Thomas Villmann: How to process uncertainty in machine learning?. ESANN 2007: 79-90
70		Thomas Villmann, Frank-Michael Schleif, Martijn van der Werff, André M. Deelder, Rob A. E. M. Tollenaar: Association Learning in SOMs for Fuzzy-Classification. ICMLA 2007: 581-586
69		Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert: Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882
68		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Supervised Neural Gas for Classification of Functional Data and Its Application to the Analysis of Clinical Proteom Spectra. IWANN 2007: 1036-1044
67		Alexander Hasenfuss, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann: Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes. IWANN 2007: 539-546
66		Thomas Villmann, Frank-Michael Schleif, Erzsébet Merényi, Barbara Hammer: Fuzzy Labeled Self-Organizing Map for Classification of Spectra. IWANN 2007: 556-563
65		Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann: 07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology. Similarity-based Clustering and its Application to Medicine and Biology 2007
64		Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann: 07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology. Similarity-based Clustering and its Application to Medicine and Biology 2007
63		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps. WILF 2007: 563-570
62		Erzsébet Merényi, Abha Jain, Thomas Villmann: Explicit Magnification Control of Self-Organizing Maps for "Forbidden" Data. IEEE Transactions on Neural Networks 18(3): 786-797 (2007)
61		Frank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin-based active learning for LVQ networks. Neurocomputing 70(7-9): 1215-1224 (2007)
60		Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. Neurocomputing 70(7-9): 1225-1234 (2007)
	2006
59		Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann: Supervised Batch Neural Gas. ANNPR 2006: 33-45
58		Thomas Villmann, Udo Seiffert, Frank-Michael Schleif, Cornelia Brüß, Tina Geweniger, Barbara Hammer: Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. ANNPR 2006: 46-56
57		Thomas Villmann, Barbara Hammer, Udo Seiffert: Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. BioADIT 2006: 141-159
56		Frank-Michael Schleif, Thomas Elssner, Markus Kostrzewa, Thomas Villmann, Barbara Hammer: Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps. CBMS 2006: 919-924
55		Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann: Neural networks and machine learning in bioinformatics - theory and applications. ESANN 2006: 521-532
54		Frank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin based Active Learning for LVQ Networks. ESANN 2006: 539-544
53		Cornelia Brüß, Felix Bollenbeck, Frank-Michael Schleif, Winfriede Weschke, Thomas Villmann, Udo Seiffert: Fuzzy image segmentation with Fuzzy Labelled Neural Gas. ESANN 2006: 563-568
52		Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. ESANN 2006: 7-12
51		Barbara Hammer, Thomas Villmann, Frank-Michael Schleif, Cornelia Albani, Wieland Hermann: Learning Vector Quantization Classification with Local Relevance Determination for Medical Data. ICAISC 2006: 603-612
50		Thomas Villmann, Barbara Hammer, Frank-Michael Schleif, Tina Geweniger, Tom Fischer, Marie Cottrell: Prototype Based Classification Using Information Theoretic Learning. ICONIP (2) 2006: 40-49
49		Thomas Villmann, Jens Christian Claussen: Magnification Control in Self-Organizing Maps and Neural Gas. Neural Computation 18(2): 446-469 (2006)
48		Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Comparison of relevance learning vector quantization with other metric adaptive classification methods. Neural Networks 19(5): 610-622 (2006)
47		Marie Cottrell, Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Batch and median neural gas. Neural Networks 19(6-7): 762-771 (2006)
46		Thomas Villmann, Barbara Hammer, Frank-Michael Schleif, Tina Geweniger, Wieland Hermann: Fuzzy classification by fuzzy labeled neural gas. Neural Networks 19(6-7): 772-779 (2006)
45		Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing 69(16-18): 2425-2428 (2006)
44		Marc Strickert, Udo Seiffert, Nese Sreenivasulu, Winfriede Weschke, Thomas Villmann, Barbara Hammer: Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis. Neurocomputing 69(7-9): 651-659 (2006)
	2005
43		Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Relevance learning for mental disease classification. ESANN 2005: 139-144
42		Barbara Hammer, Thomas Villmann: Classification using non-standard metrics. ESANN 2005: 303-316
41		Marc Strickert, Nese Sreenivasulu, Winfriede Weschke, Udo Seiffert, Thomas Villmann: Generalized Relevance LVQ with Correlation Measures for Biological Data. ESANN 2005: 331-338
40		Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning. ICMLA 2005
39		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. WILF 2005: 290-296
38		Barbara Hammer, Marc Strickert, Thomas Villmann: Supervised Neural Gas with General Similarity Measure. Neural Processing Letters 21(1): 21-44 (2005)
37		Barbara Hammer, Marc Strickert, Thomas Villmann: On the Generalization Ability of GRLVQ Networks. Neural Processing Letters 21(2): 109-120 (2005)
36		Marie Cottrell, Barbara Hammer, Thomas Villmann: New Aspects in Neurocomputing. Neurocomputing 63: 1-3 (2005)
35		Jens Christian Claussen, Thomas Villmann: Magnification control in winner relaxing neural gas. Neurocomputing 63: 125-137 (2005)
34		Jochen J. Steil, Gavin C. Cawley, Thomas Villmann: Trends in Neurocomputing at ESANN 2004. Neurocomputing 64: 1-4 (2005)
	2004
33		Thomas Villmann, Udo Seiffert, Axel Wismüller: Theory and applications of neural maps. ESANN 2004: 25-38
32		Barbara Hammer, Marc Strickert, Thomas Villmann: Relevance LVQ versus SVM. ICAISC 2004: 592-597
31		Frank-Michael Schleif, U. Clauss, Thomas Villmann, Barbara Hammer: Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data. ICMLA 2004: 374-379
30		Thomas Villmann: Special issue on new aspects in neurocomputing. Neurocomputing 57: 1-2 (2004)
29		Thomas Villmann, Beate Villmann, Volker Slowik: Evolutionary algorithms with neighborhood cooperativeness according to neural maps. Neurocomputing 57: 151-169 (2004)
	2003
28		Barbara Hammer, Thomas Villmann: Mathematical Aspects of Neural Networks. ESANN 2003: 59-72
27		Jens Christian Claussen, Thomas Villmann: Magnification Control in Winner Relaxing Neural Gas. ESANN 2003: 93-98
26		Thomas Villmann, Erzsébet Merényi, Barbara Hammer: Neural maps in remote sensing image analysis. Neural Networks 16(3-4): 389-403 (2003)
	2002
25		Axel Wismüller, Thomas Villmann: Exploratory Data Analysis in Medicine and Bioinformatics. ESANN 2002: 25-38
24		Barbara Hammer, Thomas Villmann: Batch-RLVQ. ESANN 2002: 295-300
23		Barbara Hammer, Marc Strickert, Thomas Villmann: Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376
22		Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883
21		Jutta Huhse, Thomas Villmann, Peter Merz, Andreas Zell: Evolution Strategy with Neighborhood Attraction Using a Neural Gas Approach. PPSN 2002: 391-400
20		Barbara Hammer, Thomas Villmann: Generalized relevance learning vector quantization. Neural Networks 15(8-9): 1059-1068 (2002)
19		Thomas Villmann: Neural maps for faithful data modelling in medicine - state-of-the-art and exemplary applications. Neurocomputing 48(1-4): 229-250 (2002)
	2001
18		Thomas Villmann: Evolutionary algorithms and neural networks in hybrid systems. ESANN 2001: 137-152
17		Barbara Hammer, Thomas Villmann: Input pruning for neural gas architectures. ESANN 2001: 283-288
16		Thomas Villmann, Conny Albani: Clustering of Categoric Data in Medicine - Application of Evolutionary Algorithms. Fuzzy Days 2001: 619-627
	2000
15		Thomas Villmann: Neural networks approaches in medicine - a review of actual developments. ESANN 2000: 165-176
14		Thomas Villmann, R. Haupt, Klaus Hering: Parallel Evolutionary Algorithms with SOM-Like Migration and its Application to VLSI-Design. IJCNN (5) 2000: 167-172
13		Thomas Villmann, Wieland Hermann, Michael Geyer: Data Mining and Knowledge Discovery in Medical Applications Using Self-Organizing Maps. ISMDA 2000: 138-151
	1999
12		Thomas Villmann: Benefits and limits of the self-organizing map and its variants in the area of satellite remote sensoring processing. ESANN 1999: 111-116
11		Hans-Ulrich Bauer, J. Michael Herrmann, Thomas Villmann: Neural maps and topographic vector quantization. Neural Networks 12(4-5): 659-676 (1999)
	1998
10		Thomas Villmann, J. Michael Herrmann: Magnification control in neural maps. ESANN 1998: 191-196
9		Thomas Villmann, A. Körner, Conny Albani: Evolutionary Algorithms with Self-Organizing Population Dynamic for Clustering of Categories in Psychotherapy Research Using Large Clinical Data Sets. NC 1998: 130-136
8		Thomas Villmann, Hans-Ulrich Bauer: Applications of the growing self-organizing map. Neurocomputing 21(1-3): 91-100 (1998)
	1997
7		J. Michael Herrmann, Hans-Ulrich Bauer, Thomas Villmann: Measuring topology preservation in maps of real-world data. ESANN 1997
6		Thomas Villmann, Beate Villmann, Conny Albani: Application of Evolutionary Algorithms to the Problem of New Clustering of Psychological Categories Using Real Clinical Data Sets. Fuzzy Days 1997: 311-320
5		J. Michael Herrmann, Thomas Villmann: Vector Quantization by Optimal Neural Gas. ICANN 1997: 625-630
4		Ralf Der, M. Herrmann, Thomas Villmann: Time behavior of topological ordering in self-organizing feature mapping. Biological Cybernetics 77(6): 419-427 (1997)
	1996
3		Klaus Hering, R. Haupt, Thomas Villmann: Hierarchical Strategy of Model Partitioning for VLSI-Design Using an Improved Mixture of Experts Approach. Workshop on Parallel and Distributed Simulation 1996: 106-113
	1994
2		Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz: Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement. Fuzzy Days 1994: 159-166
	1993
1		Ralf Der, Thomas Villmann: Dynamics of Self-Organized Feature Mapping. IWANN 1993: 312-315

Coauthor Index

1	Jennifer R. Aduwo	[113]
2	Conny Albani	[6] [9] [16]
3	Cornelia Albani	[51]
4	Alán Alpár	[111]
5	Andreas Backhaus	[118]
6	Hans-Ulrich Bauer	[7] [8] [11]
7	Michael Biehl	[64] [65] [73] [79] [85] [88] [94] [95] [100] [103] [104] [109] [110] [112] [113] [114] [117] [122] [126] [127]
8	Felix Bollenbeck	[53]
9	Cornelia Brüß	[53] [58] [72]
10	Kerstin Bunte	[103] [109] [114] [124] [127]
11	Gavin C. Cawley	[34]
12	Andrzej Cichocki	[125]
13	U. Clauss	[31]
14	Jens Christian Claussen	[27] [35] [49]
15	Marie Cottrell	[36] [47] [50]
16	André M. Deelder	[70] [77]
17	Ralf Der	[1] [2] [4]
18	Thomas Elssner	[56] [96]
19	Tom Fischer	[50]
20	Alexander Gammerman (Alex J. Gammerman)	[87]
21	Ulrich Gärtner	[111]
22	Tina Geweniger	[46] [50] [58] [78] [81] [90] [98] [99] [101] [107] [108] [118] [121] [122] [128]
23	Michael Geyer	[13]
24	Sven Haase	[105] [107] [110] [112] [113] [115] [118] [120] [124]
25	Barbara Hammer	[17] [20] [22] [23] [24] [26] [28] [31] [32] [36] [37] [38] [39] [40] [42] [43] [44] [45] [46] [47] [48] [50] [51] [52] [54] [55] [56] [57] [58] [59] [60] [61] [63] [64] [65] [66] [67] [68] [69] [71] [73] [75] [76] [77] [78] [81] [84] [85] [87] [88] [89] [90] [91] [94] [98] [100] [101] [102] [103] [104] [105] [106] [109] [112] [114] [116] [117] [126] [127]
26	Alexander Hasenfuss (Alexander Hasenfuß)	[47] [52] [59] [60] [67] [69] [78] [81]
27	R. Haupt	[3] [14]
28	Ulrich Heimann	[99]
29	Klaus Hering	[3] [14]
30	Wieland Hermann	[13] [46] [51]
31	J. Michael Herrmann	[2] [5] [7] [10] [11]
32	M. Herrmann	[4]
33	Jutta Huhse	[21]
34	Abha Jain	[62]
35	Samuel Kaski	[55]
36	Marika Kästner	[118] [119] [121] [126] [128] [129]
37	Jens Keilwagen	[85] [95]
38	Andreas Kolb	[123]
39	A. Körner	[9]
40	Markus Kostrzewa	[56] [76] [87] [92]
41	Björn Labitzke	[123]
42	Mandy Lange	[128]
43	Thomas Martinetz	[2]
44	Erzsébet Merényi	[26] [62] [66] [80] [117]
45	Peter Merz	[21]
46	Ernest Mwebaze	[110] [113]
47	Matthias Ongyerth	[83] [86]
48	José Carlos Príncipe (José C. Príncipe, Jose C. Principe)	[125]
49	John A. Quinn (John Alexander Quinn)	[113]
50	Andreas Rechtien	[22] [43]
51	Andreas Schierwagen	[111]
52	Frank-Michael Schleif	[31] [39] [40] [45] [46] [48] [50] [51] [53] [54] [56] [58] [59] [61] [63] [66] [67] [68] [69] [70] [72] [74] [75] [76] [77] [78] [79] [82] [83] [86] [87] [89] [92] [93] [95] [96] [97] [102] [104] [105] [106] [107] [110] [112] [113] [116] [122] [124] [127]
53	Petra Schneider	[79] [85] [88] [103] [104] [110] [113] [116] [122] [127]
54	Udo Seiffert	[33] [41] [44] [53] [55] [57] [58] [69] [72] [74] [80] [93] [118]
55	Stephan Simmuteit	[92] [96] [102]
56	Volker Slowik	[29]
57	Alessandro Sperduti	[117]
58	Nese Sreenivasulu	[41] [44] [84]
59	Jochen J. Steil (Jochen Jakob Steil)	[34]
60	Han Stiekema	[103]
61	Marc Strickert	[22] [23] [32] [37] [38] [41] [43] [44] [69] [72] [74] [82] [84] [85] [93] [95] [123]
62	Rob A. E. M. Tollenaar	[70] [77]
63	Michel Verleysen	[64] [65] [73] [100]
64	Beate Villmann	[6] [29]
65	Axel Walch	[76]
66	Martijn van der Werff	[70] [77]
67	Winfriede Weschke	[41] [44] [53]
68	Axel Wismüller	[25] [33] [109] [114]
69	Andreas Zell	[21]
70	Dietlind Zühlke	[90] [98] [99] [101] [107]

Colors in the list of coauthors

Last update Fri May 25 01:42:58 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page