Distributed Anomaly Detection of Single Mote Attacks in RPL Networks. - Nicolas M. Müller; Pascal Debus; Daniel Kowatsch; Konstantin Böttinger (ICETE (2), 2019)

On GDPR Compliance of Companies' Privacy Policies. - Nicolas M. Müller; Daniel Kowatsch; Pascal Debus; Donika Mirdita; Konstantin Böttinger (TSD, 2019)

Deep Reinforcement Learning for Backup Strategies against Adversaries. - Pascal Debus; Nicolas M. Müller; Konstantin Böttinger (CoRR, 2021)

Fairness in Regression - Analysing a Job Candidates Ranking System. - Karla Markert; Afrae Ahouzi; Pascal Debus (GI-Jahrestagung, 2022)

Protecting Publicly Available Data With Machine Learning Shortcuts. - Nicolas M. Müller; Maximilian Burgert; Pascal Debus; Jennifer Williams 001; Philip Sperl; Konstantin Böttinger (BMVC, 2023)

Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel. - Kilian Tscharke; Sebastian Issel; Pascal Debus (QCE, 2023)

Towards Efficient Quantum Anomaly Detection: One-Class SVMs Using Variable Subsampling and Randomized Measurements. - Michael Kölle 001; Afrae Ahouzi; Pascal Debus; Robert Müller 005; Daniëlle Schuman; Claudia Linnhoff-Popien (ICAART (2), 2024)

QUACK: Quantum Aligned Centroid Kernel. - Kilian Tscharke; Sebastian Issel; Pascal Debus (QCE, 2024)

A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models. - Maximilian Wendlinger; Kilian Tscharke; Pascal Debus (QCE, 2024)

Quantum Machine Learning Playground. - Pascal Debus; Sebastian Issel; Kilian Tscharke (IEEE Computer Graphics and Applications, 2024)

Towards Classical Software Verification using Quantum Computers. - Sebastian Issel; Kilian Tscharke; Pascal Debus (CoRR, 2024)

Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling. - Michael Kölle 001; Afrae Ahouzi; Pascal Debus; Elif Çetiner; Robert Müller 005; Daniëlle Schuman; Claudia Linnhoff-Popien (CoRR, 2024)

Quantum Autoencoder for Multivariate Time Series Anomaly Detection. - Kilian Tscharke; Maximilian Wendlinger; Afrae Ahouzi; Pallavi Bhardwaj; Kaweh Amoi-Taleghani; Michael Schrödl-Baumann; Pascal Debus (CoRR, 2025)

Quantum Support Vector Regression for Robust Anomaly Detection. - Kilian Tscharke; Maximilian Wendlinger; Sebastian Issel; Pascal Debus (CoRR, 2025)

Entangled Threats: A Unified Kill Chain Model for Quantum Machine Learning Security. - Pascal Debus; Maximilian Wendlinger; Kilian Tscharke; Daniel Herr; Cedric Brügmann; Daniel Ohl de Mello; Juris Ulmanis; Alexander Erhard; Arthur Schmidt; Fabian Petsch (CoRR, 2025)

Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning. - Maximilian Wendlinger; Kilian Tscharke; Pascal Debus (CoRR, 2025)