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

Frequently cited papers (only 2007-2017)
according to Thomson Web of Science, as of January 2018

Among the top 1% of their year ...

... in Computer Science:

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

... 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)

... 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)

... 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)

W. Arlt, K. Lang, A. Sitch et al.
Steroid metabolome analysis reveals prevalent glucocorticoid excess in primary aldosteroinism
J. of Clinical Investigation JCI Insight 2(8), 2017 (online, open access)

Among the top 10% of their year in ...

... in Clinical Medicine:

L. Yeo, N. Adlard, M. Biehl, M. Juarez, T. Smallie, M. Snow, C.D. Buckley, K. Raza, A. File, D. Scheel-Toellner
Expression of Chemokines CXCL4 and CXCL7 by synovial macrophages defines an early stage of rheumatoid arthritis
Annals of the Rheumatic Diseases 75: 763-771 (2015))

... 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) Computer Science:

M. Biehl, B. Hammer, T. Villmann
Prototype-based models in machine learning
Wiley Interdisciplinary Reviews (WIRES): Cognitive Science (2016)

I. Giotis, N. Molders, S. Land, M. Biehl, M.F. Jonkman, N. Petkov
MED-NODE: a computer-assisted melanoma diagnosis system using non-dermoscopic images
Expert Systems with Applications 42(19): 6578-6585 (2015)

G.-J. de Vries, S. Pauws, M. Biehl
Insightful stress detection from physiology modalities using Learning Vector Quantization
Neurocomputing 151: 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, S. Haase, M. Biehl, T. Villmann
Stochastic Neighbor Embedding (SNE) for Dimension Reduction and Visualization using arbitrary Divergences
Neurocomputing 40:23-45 (2012)

E. Mwebaze, P. Schneider, F.-M. Schleif, J.R. Aduwo, J.A. Quinn, S. Haase, T. Villmann, M. Biehl
Divergence-based classification in Learning Vector Quantization
Neurocomputing 74: 1429-1435 (2011)

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
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)