click here to return to homepage Michael Biehl, Intelligent Systems, frequently cited papers in CS


Frequently cited papers (only 2006-2016)
according to Thomson Web of Science, as of November 2016

Among the top 1% of their year in Biology and Biochemistry:

N. Aghaeepour, G. Finak, H. Hoos, et al.
Critical assessment of automated flow cytometry data analysis techniqes
Nature Methods 10, 228-238 (2013)

Among the top 1% of their year in Molecular Biology and Genetics:

C.F. Davies, C.J. Ricketts, M. Wang et al.
The Somatic Genomic Landscape of Chromophobe Renal Cell Carcinoma
Cancer Cell 26: 319-330 (2014)

Among the top 10% of their year in Clinical Medicine:

W. Arlt, M. Biehl, A.E. Taylor et al.
Urine steroid metabolomics as a biomarker tool for detecting malignancy in adrenal tumors
J. of Clinical Endocrinology and Metabolism 96, 375-3784 (2011)

Among the top 10% of their year in Space Sciences:

A. Offringa, A.G. De Bruyn, M. Biehl et al.
Post-correlation radio frequency interference classification methods
Monthly Notices of the Royal Astronomical Society 405, 155-167 (2010)

Among the top 10% of their year in Computer Science:

G.-J. de Vries, S. Pauws, M. Biehl
Insightful stress detection from physiology modalities using Learning Vector Quantization
Neurocomputing151: 873-882 (2015))

M. Biehl, K. Bunte, P. Schneider
Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization
Plos One 8 (2013)

K. Bunte, M. Biehl, B. Hammer
A General Framework for Dimensionality-Reducing Data Visualzation Mapping
Neural Computation 24: 771-804 (2012)

K. Bunte, P. Schneider, B. Hammer, F.-M. Schleif, T. Villmann, M. Biehl
Limited Rank Matrix Learning, discriminative dimension reduction and visualization
Neural Networks 26: 159-173 (2012)

K. Bunte, M. Biehl, M.F. Jonkman, N. Petkov
Learning Effective Color Features for Content Based Image Retrieval in Dermatology
Pattern Recognition 44: 1892-1902 (2011)

K. Bunte, B. Hammer, T. Villmann, M. Biehl, A. Wismüller
Neighbor Embedding XOM for dimension reduction and visualization
Neurocomputing 74: 1340-1350 (2011)

K. Bunte, B. Hammer, A. Wismüller et al.
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data
Neurocomputing 73: 1074-1092 (2010)

P. Schneider, K. Bunte, H. Stiekema, B. Hammer, T. Villmann, M. Biehl
Regularization in Matrix Relevance Learning
IEEE Trans. Neural Networks 21, 831-840 (2010)

P. Schneider, M. Biehl, B. Hammer
Adaptive Relevance Matrices in Learning Vector Quantization
Neural Computation 21, 3532-3561 (2009)

P. Schneider, M. Biehl, B. Hammer
Distance Learning in Discriminative Vector Quantization
Neural Computation 21, 2942-2969 (2009)

M. Biehl, A. Ghosh, and B. Hammer
Dynamics and generalization ability of LVQ algorithms
J. Machine Learning Research 8:323-360 (2007)

M.Biehl, A. Ghosh, and B. Hammer
Learning Vector Quantization: the dynamics of Winner-Takes-All algorithms
Neurocomputing 69: 660-670 (2006)