Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features. - Katrin Sophie Bohnsack; Marika Kaden; Julius Voigt; Thomas Villmann (ESANN, 2022)

Multi-proximity based embedding scheme for learning vector quantization-based classification of biochemical structured data. - Katrin Sophie Bohnsack; Julius Voigt; Marika Kaden; Florian Heinke; Thomas Villmann (Neurocomputing, 2023)

Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge. - Julius Voigt; Sascha Saralajew; Marika Kaden; Katrin Sophie Bohnsack; Lynn V. Reuss; Thomas Villmann (BIOSTEC (1), 2024)

Knowledge Integration in Vector Quantization Models and Corresponding Structured Covariance Estimation. - Marika Kaden; Julius Voigt; Katrin Sophie Bohnsack; Mandy Lange-Geisler; Thomas Villmann (WSOM+, 2024)