Andreas Rauber

The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data

Content-based organization and visualization of music archives

The growing hierarchical self-organizing map

Evaluation Of Feature Extractors And Psycho-Acoustic Transformations For Music Genre Classification.

Achieving human and machine accessibility of cited data in scholarly publications

Uncovering hierarchical structure in data using the growing hierarchical self-organizing map

LifeCLEF 2015: Multimedia Life Species Identification Challenges

Visual Methods for Analyzing Probabilistic Classification Data

Systematic planning for digital preservation: evaluating potential strategies and building preservation plans

I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences

System log clustering approaches for cyber security applications: A survey

Using smoothed data histograms for cluster visualization in Self-Organizing Maps