Villmann T - Search Results

1

Application of an interpretable classification model on Early Folding Residues during protein folding.

Bittrich S, Kaden M, Leberecht C, Kaiser F, Villmann T, Labudde D. Bittrich S, et al. Among authors: villmann t. BioData Min. 2019 Jan 5;12:1. doi: 10.1186/s13040-018-0188-2. eCollection 2019. BioData Min. 2019. PMID: 30627219 Free PMC article.

2

Clustering by fuzzy neural gas and evaluation of fuzzy clusters.

Geweniger T, Fischer L, Kaden M, Lange M, Villmann T. Geweniger T, et al. Among authors: villmann t. Comput Intell Neurosci. 2013;2013:165248. doi: 10.1155/2013/165248. Epub 2013 Dec 16. Comput Intell Neurosci. 2013. PMID: 24396342 Free PMC article.

3

Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences.

Kaden M, Bohnsack KS, Weber M, Kudła M, Gutowska K, Blazewicz J, Villmann T. Kaden M, et al. Among authors: villmann t. Neural Comput Appl. 2022;34(1):67-78. doi: 10.1007/s00521-021-06018-2. Epub 2021 Apr 27. Neural Comput Appl. 2022. PMID: 33935376 Free PMC article.

4

AI-Based Multi Sensor Fusion for Smart Decision Making: A Bi-Functional System for Single Sensor Evaluation in a Classification Task.

Zoghlami F, Kaden M, Villmann T, Schneider G, Heinrich H. Zoghlami F, et al. Among authors: villmann t. Sensors (Basel). 2021 Jun 27;21(13):4405. doi: 10.3390/s21134405. Sensors (Basel). 2021. PMID: 34199090 Free PMC article.

5

The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers.

Bohnsack KS, Kaden M, Abel J, Saralajew S, Villmann T. Bohnsack KS, et al. Among authors: villmann t. Entropy (Basel). 2021 Oct 17;23(10):1357. doi: 10.3390/e23101357. Entropy (Basel). 2021. PMID: 34682081 Free PMC article.

6

Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective.

Bohnsack KS, Kaden M, Abel J, Villmann T. Bohnsack KS, et al. Among authors: villmann t. IEEE/ACM Trans Comput Biol Bioinform. 2023 Jan-Feb;20(1):119-135. doi: 10.1109/TCBB.2022.3140873. Epub 2023 Feb 3. IEEE/ACM Trans Comput Biol Bioinform. 2023. PMID: 34990369

7

Quantum Computing Approaches for Vector Quantization-Current Perspectives and Developments.

Engelsberger A, Villmann T. Engelsberger A, et al. Among authors: villmann t. Entropy (Basel). 2023 Mar 21;25(3):540. doi: 10.3390/e25030540. Entropy (Basel). 2023. PMID: 36981428 Free PMC article.

8

Divergence-based vector quantization.

Villmann T, Haase S. Villmann T, et al. Neural Comput. 2011 May;23(5):1343-92. doi: 10.1162/NECO_a_00110. Epub 2011 Feb 7. Neural Comput. 2011. PMID: 21299418

9

Prototype-based models in machine learning.

Biehl M, Hammer B, Villmann T. Biehl M, et al. Among authors: villmann t. Wiley Interdiscip Rev Cogn Sci. 2016 Mar-Apr;7(2):92-111. doi: 10.1002/wcs.1378. Epub 2016 Jan 21. Wiley Interdiscip Rev Cogn Sci. 2016. PMID: 26800334 Review.

10

Fuzzy classification by fuzzy labeled neural gas.

Villmann T, Hammer B, Schleif F, Geweniger T, Herrmann W. Villmann T, et al. Neural Netw. 2006 Jul-Aug;19(6-7):772-9. doi: 10.1016/j.neunet.2006.05.026. Epub 2006 Jul 3. Neural Netw. 2006. PMID: 16815673

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