Post-Robustifying Deep Anomaly Detection Ensembles by Model Selection. - Benedikt Böing; Simon Klüttermann; Emmanuel Müller (ICDM, 2022)

Towards Graph Representation based Re-Identification of Chipwood Pallet Blocks. - Simon Klüttermann; Jérôme Rutinowski; Christopher Reining; Moritz Roidl; Emmanuel Müller (ICMLA, 2022)

On Graph Representation based Re-Identification - A Proof of Concept. - Simon Klüttermann; Jérôme Rutinowski; Anh Nguyen; Christopher Reining; Moritz Roidl; Emmanuel Müller (ICDM (Workshops), 2023)

Evaluating and Comparing Heterogeneous Ensemble Methods for Unsupervised Anomaly Detection. - Simon Klüttermann; Emmanuel Müller (IJCNN, 2023)

A Laser-based Volumetric Measurement Approach for Industrial Settings. - Jérôme Rutinowski; Niklas Schrötler; Simon Klüttermann; Moritz Roidl; Christian Janiesch (CASE, 2024)

Towards Highly Efficient Anomaly Detection for Predictive Maintenance. - Simon Klüttermann; Vanlal Peka; Philipp Doebler; Emmanuel Müller (ICMLA, 2024)

On the Effectiveness of Heterogeneous Ensemble Methods for Re-Identification. - Simon Klüttermann; Jérôme Rutinowski; Frederik Polachowski; Anh Nguyen; Britta Grimme; Moritz Roidl; Emmanuel Müller (ICMLA, 2024)

Evaluating Anomaly Detection Algorithms: A Multi-Metric Analysis Across Variable Class Imbalances. - Mohammad-Sahadet Hossain; Mohammad Sakhawat Hossain; Simon Klüttermann; Emmanuel Müller (IJCNN, 2024)

The Phenomenon of Correlated Representations in Contrastive Learning. - Simon Klüttermann; Jérôme Rutinowski; Emmanuel Müller (IJCNN, 2024)

Autoencoder Optimization for Anomaly Detection: A Comparative Study with Shallow Algorithms. - Vikas Kumar; Vishesh Srivastava; Sadia Mahjabin; Arindam Pal 003; Simon Klüttermann; Emmanuel Müller (IJCNN, 2024)

On the Efficient Explanation of Outlier Detection Ensembles Through Shapley Values. - Simon Klüttermann; Chiara Balestra; Emmanuel Müller (PAKDD (3), 2024)

Benchmarking Trust: A Metric for Trustworthy Machine Learning. - Jérôme Rutinowski; Simon Klüttermann; Jan Endendyk; Christopher Reining; Emmanuel Müller (xAI (1), 2024)

On the Effectiveness of Heterogeneous Ensemble Methods for Re-identification. - Simon Klüttermann; Jérôme Rutinowski; Anh Nguyen; Britta Grimme; Moritz Roidl; Emmanuel Müller (CoRR, 2024)

About Test-time training for outlier detection. - Simon Klüttermann; Emmanuel Müller (CoRR, 2024)

Exploring the Impact of Outlier Variability on Anomaly Detection Evaluation Metrics. - Minjae Ok; Simon Klüttermann; Emmanuel Müller (CoRR, 2024)

Unsupervised Surrogate Anomaly Detection. - Simon Klüttermann; Tim Katzke; Emmanuel Müller (CoRR, 2025)

Polyra Swarms: A Shape-Based Approach to Machine Learning. - Simon Klüttermann; Emmanuel Müller (CoRR, 2025)

We Need to Rethink Benchmarking in Anomaly Detection. - Philipp Röchner; Simon Klüttermann; Franz Rothlauf; Daniel Schlör (CoRR, 2025)

Rare anomalies require large datasets: About proving the existence of anomalies. - Simon Klüttermann; Emmanuel Müller (CoRR, 2025)