Publications

This page lists my publications and other research contributions, including conference and journal papers, workshop papers, software, and technical reports.

For citation records, see Google Scholar and DBLP.

On Challenging Aspects of Reproducibility in Deep Anomaly Detection (13 Jul. 2022)
Our companion paper, On Challenging Aspects of Reproducibility in Deep Anomaly Detection, has been accepted for presentation at the Fourth Workshop on Reproducible Research in Pattern Recognition (satellite event of ICPR 2022). In it, we discuss aspects of reproducibility for our anomaly detection algorithm MCHAD, as well as anomaly detection with deep neural networks in general. In particular, we discussed the following challenges for reproducibility: Nondeterminism: conducting the same …
Paper
Categories: Anomaly Detection Reproducibility
207 Words Tagged with: ICPR Anomaly Detection Reproducibility
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PyTorch-OOD: A library for Out-of-Distribution Detection based on PyTorch (13 Jul. 2022)
Our paper, PyTorch-OOD: A library for Out-of-Distribution Detection based on PyTorch, has been presented at the CVPR 2022 Workshops. You can find the most recent version of the Python source code on GitHub. The library has developed substantially since the original 2022 paper. The current release, documentation, and supported methods are available through the project links below: GitHub · Documentation · PyPI. Abstract § Machine Learning models based on Deep Neural Networks behave unpredictably …
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Code
Slides
Categories: Anomaly Detection
247 Words Tagged with: CVPR Anomaly Detection
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Addressing Randomness in Evaluation Protocols for Out-of-Distribution Detection (13 Jul. 2021)
Our paper Addressing Randomness in Evaluation Protocols for Out-of-Distribution Detection has been accepted at the IJCAI 2021 Workshop for Artificial Intelligence for Anomalies and Novelties. In summary, we investigated the following phenomenon: when you train neural networks several times, and then measure their performance on some task, there is a certain variance in the performance measurements, since the results of experiments may vary based on several factors (that are effectively …
Paper
Categories: Anomaly Detection Reproducibility
252 Words Tagged with: IJCAI Anomaly Detection Reproducibility
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Data-Mining als Werkzeug empirischer Sozialforschung (13 Jul. 2020)
Inspired by David Kriesel’s talk “Spiegel-Mining”, a friend of mine and a professor from the Hochschule Magdeburg scraped a German website that regularly publishes reviews of social work literature and mined the resulting 18.000 articles, hoping for interesting insights. In an attempt to visualize the discourse, we created several topic maps, like the one below, which you can find on the accompanying (German) website. The colors represent the gender of the authors of the …
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Code
Categories: Data Mining
146 Words Tagged with: Sozial Extra Data Mining
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Explanation-based Anomaly Detection in Deep Neural Networks (01 Feb. 2020)
Masters Thesis (PDF). If an AI gives you a weird explanation for its prediction, you should remain skeptical about the accuracy of the prediction. Sounds reasonable? This was the general idea of my masters thesis, which was originally titled Self-Assessment of Visual Recognition Systems based on Attribution. Today, I would call it Explanation-based Anomaly Detection in Deep Neural Networks. The general idea was to use attribution-based explanation methods to detect anomalies (such as unusual …
Paper
Categories: Anomaly Detection
340 Words Tagged with: Deep Learning Anomaly Detection CNN Explainability
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