Marika Kaden

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 47

Top Topics

Structured Data

Learning Vector Quantization

Multi Sensor Fusion

Top Venues

Neural Comput. Appl.

Publications

Julius Voigt, Sascha Saralajew, Marika Kaden, Katrin Sophie Bohnsack, Lynn V. Reuss, Thomas Villmann
Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge. BIOSTEC (1) (2024)
Katrin Sophie Bohnsack, Julius Voigt, Marika Kaden, Florian Heinke, Thomas Villmann
Multi-proximity based embedding scheme for learning vector quantization-based classification of biochemical structured data. Neurocomputing 554 (2023)
Ronny Schubert, Lynn V. Reuss, Daniel Staps, Marika Kaden, Thomas Villmann, Robert Hasler, Robin Herz, Till Tiemann, Wolfram Richardt
A White-Box Workflow for the Prediction of Food Content From Near-Infrared Data Based on Fourier-Transformation. WHISPERS (2023)
Katrin Sophie Bohnsack, Marika Kaden, Julia Abel, Thomas Villmann
Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (1) (2023)
Daniel Staps, Marika Kaden, Jan Auth, Florian Zaussinger, Thomas Villmann
Compression of Particle Images for Inspection of Microgravity Experiments by Means of a Symmetric Structural Auto-Encoder. WHISPERS (2023)
Katrin Sophie Bohnsack, Alexander Engelsberger, Marika Kaden, Thomas Villmann
Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings. BIOINFORMATICS (2023)
Thomas Villmann, Ronny Schubert, Marika Kaden
Variants of Neural Gas for Regression Learning. ESANN (2023)
Katrin Sophie Bohnsack, Marika Kaden, Julius Voigt, Thomas Villmann
Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features. ESANN (2022)
Thomas Villmann, Daniel Staps, Jensun Ravichandran, Sascha Saralajew, Michael Biehl, Marika Kaden
A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Null-Space Evaluation. IDA (2022)
Marika Kaden, Katrin Sophie Bohnsack, Mirko Weber, Mateusz Kudla, Kaja Gutowska, Jacek Blazewicz, Thomas Villmann
Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences. Neural Comput. Appl. 34 (1) (2022)
Jensun Ravichandran, Marika Kaden, Thomas Villmann
Variants of recurrent learning vector quantization. Neurocomputing 502 (2022)
Daniel Staps, Ronny Schubert, Marika Kaden, Alexander Lampe, Wieland Hermann, Thomas Villmann
Prototype-based One-Class-Classification Learning Using Local Representations. IJCNN (2022)
Danny Möbius, Jensun Ravichandran, Marika Kaden, Thomas Villmann
Trustworthiness and Confidence of Gait Phase Predictions in Changing Environments Using Interpretable Classifier Models. ICONIP (2) (2022)
Thomas Villmann, Alexander Engelsberger, Jensun Ravichandran, Andrea Villmann, Marika Kaden
Quantum-inspired learning vector quantizers for prototype-based classification. Neural Comput. Appl. 34 (1) (2022)
Seyedfakhredin Musavishavazi, Marika Kaden, Thomas Villmann
Possibilistic Classification Learning Based on Contrastive Loss in Learning Vector Quantizer Networks. ICAISC (1) (2021)
Katrin Sophie Bohnsack, Marika Kaden, Julia Abel, Sascha Saralajew, Thomas Villmann
The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy 23 (10) (2021)
Marika Kaden, Ronny Schubert, Mehrdad Mohannazadeh Bakhtiari, Lucas Schwarz, Thomas Villmann
The LVQ-based Counter Propagation Network - an Interpretable Information Bottleneck Approach. ESANN (2021)
Jensun Ravichandran, Thomas Villmann, Marika Kaden
RecLVQ: Recurrent Learning Vector Quantization. ESANN (2021)
Feryel Zoghlami, Marika Kaden, Thomas Villmann, Germar Schneider, Harald Heinrich
AI-Based Multi Sensor Fusion for Smart Decision Making: A Bi-Functional System for Single Sensor Evaluation in a Classification Task. Sensors 21 (13) (2021)
Feryel Zoghlami, Marika Kaden, Thomas Villmann, Germar Schneider, Harald Heinrich
Sensors data fusion for smart decisions making: A novel bi-functional system for the evaluation of sensors contribution in classification problems. ICIT (2021)
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert
Learning vector quantization and relevances in complex coefficient space. Neural Comput. Appl. 32 (24) (2020)
Jensun Ravichandran, Marika Kaden, Sascha Saralajew, Thomas Villmann
Variants of DropConnect in Learning vector quantization networks for evaluation of classification stability. Neurocomputing 403 (2020)
Thomas Villmann, Jensun Ravichandran, Alexander Engelsberger, Andrea Villmann, Marika Kaden
Quantum-Inspired Learning Vector Quantization for Classification Learning. ESANN (2020)
Thomas Villmann, Marika Kaden, Szymon Wasik, Mateusz Kudla, Kaja Gutowska, Andrea Villmann, Jacek Blazewicz
Searching for the Origins of Life - Detecting RNA Life Signatures Using Learning Vector Quantization. WSOM+ (2019)
Thomas Villmann, Marika Kaden, Mehrdad Mohannazadeh Bakhtiari, Andrea Villmann
Appropriate Data Density Models in Probabilistic Machine Learning Approaches for Data Analysis. ICAISC (2) (2019)
Thomas Villmann, Jensun Ravichandran, Andrea Villmann, David Nebel, Marika Kaden
Investigation of Activation Functions for Generalized Learning Vector Quantization. WSOM+ (2019)
Sebastian Bittrich, Marika Kaden, Christoph Leberecht, Florian Kaiser, Thomas Villmann, Dirk Labudde
Application of an interpretable classification model on Early Folding Residues during protein folding. BioData Min. 12 (1) (2019)
Thomas Villmann, John Ravichandran, Andrea Villmann, David Nebel, Marika Kaden
Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison. CoRR (2019)
Andrea Villmann, Marika Kaden, Sascha Saralajew, Thomas Villmann
Probabilistic Learning Vector Quantization with Cross-Entropy for Probabilistic Class Assignments in Classification Learning. ICAISC (1) (2018)
Maik Benndorf, Marika Kaden, Frederic Ringsleben, Christian Roschke, Rico Thomanek, Martin Gaedke, Thomas Haenselmann
Investigating the Influence of CPU Load, Memory Usage and Environmental Conditions on the Jittering of Android Devices. ICNCC (2018)
Thomas Villmann, Marika Kaden, Wieland Hermann, Michael Biehl
Learning vector quantization classifiers for ROC-optimization. Comput. Stat. 33 (3) (2018)
Andrea Villmann, Marika Kaden, Sascha Saralajew, Wieland Hermann, Thomas Villmann
Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach. ESANN (2018)
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert
Prototypes and matrix relevance learning in complex fourier space. WSOM (2017)
Marika Kaden, David Nebel, Friedrich Melchert, Andreas Backhaus, Udo Seiffert, Thomas Villmann
Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities. WSOM (2017)
Thomas Villmann, Andrea Bohnsack, Marika Kaden
Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning. J. Artif. Intell. Soft Comput. Res. 7 (1) (2017)
David Nebel, Marika Kaden, Andrea Villmann, Thomas Villmann
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning. Neurocomputing 268 (2017)
Andrea Bohnsack, Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann
Learning matrix quantization and relevance learning based on Schatten-p-norms. Neurocomputing 192 (2016)
Kerstin Bunte, Marika Kaden, Frank-Michael Schleif
Low-Rank Kernel Space Representations in Prototype Learning. WSOM (2016)
Thomas Villmann, Marika Kaden, David Nebel, Andrea Bohnsack
Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning - A Mathematical Characterization. ICAISC (2) (2016)
Thomas Villmann, Marika Kaden, Andrea Bohnsack, J.-M. Villmann, T. Drogies, Sascha Saralajew, Barbara Hammer
Self-Adjusting Reject Options in Prototype Based Classification. WSOM (2016)
Matthias Gay, Marika Kaden, Michael Biehl, Alexander Lampe, Thomas Villmann
Complex Variants of GLVQ Based on Wirtinger's Calculus. WSOM (2016)
Marika Kaden, David Nebel, Thomas Villmann
Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities. ESANN (2016)
Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann
Learning matrix quantization and variants of relevance learning. ESANN (2015)
Marika Kaden, Martin Riedel, Wieland Hermann, Thomas Villmann
Border-sensitive learning in generalized learning vector quantization: an alternative to support vector machines. Soft Comput. 19 (9) (2015)
Andrea Bohnsack, Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann
Mathematical Characterization of Sophisticated Variants for Relevance Learning in Learning Matrix Quantization Based on Schatten-p-norms. ICAISC (1) (2015)
Thomas Villmann, Marika Kaden, David Nebel, Michael Biehl
Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection. CAIP (2) (2015)
Thomas Villmann, Sven Haase, Marika Kaden
Kernelized vector quantization in gradient-descent learning. Neurocomputing 147 (2015)
Thomas Villmann, Marika Kaden, Mandy Lange, Paul Sturmer, Wieland Hermann
Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems. CIDM (2014)
Mathias Klingner, Sven Hellbach, Martin Riedel, Marika Kaden, Thomas Villmann, Hans-Joachim Böhme
RFSOM - Extending Self-Organizing Feature Maps with Adaptive Metrics to Combine Spatial and Textural Features for Body Pose Estimation. WSOM (2014)
Thomas Villmann, Marika Kaden, David Nebel, Martin Riedel
Lateral enhancement in adaptive metric learning for functional data. Neurocomputing 131 (2014)
Marika Kaden, Wieland Hermann, Thomas Villmann
Attention Based Classification Learning in GLVQ and Asymmetric Misclassification Assessment. WSOM (2014)
Marika Kaden, Wieland Hermann, Thomas Villmann
Optimization of General Statistical Accuracy Measures for Classification Based on Learning Vector Quantization. ESANN (2014)
Tina Geweniger, Lydia Fischer, Marika Kaden, Mandy Lange, Thomas Villmann
Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters. Comput. Intell. Neurosci. 2013 (2013)