3 papers
cs.LG2026
We Need to Rethink Benchmarking in Anomaly Detection
Philipp Röchner, Simon Klüttermann, Kevin Kammler +3
Despite the continuous proposal of new anomaly detection algorithms and extensive benchmarking efforts, progress seems to stagnate, with only minor performance differences between…
q-bio.GN2026
An Imbalanced Dataset with Multiple Feature Representations for Studying Quality Control of Next-Generation Sequencing
Philipp Röchner, Clarissa Krämer, Johannes U Mayer +3
Next-generation sequencing (NGS) is a key technique for studying the DNA and RNA of organisms. However, identifying quality problems in NGS data across different experimental setti…
cs.LG2024
Robust Statistical Scaling of Outlier Scores: Improving the Quality of Outlier Probabilities for Outliers (Extended Version)
Philipp Röchner, Henrique O. Marques, Ricardo J. G. B. Campello +2
Outlier detection algorithms typically assign an outlier score to each observation in a dataset, indicating the degree to which an observation is an outlier. However, these scores…