Pascal Debus

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 14

Top Topics

Anomalous Behavior

Machine Learning

Detecting Anomalous

Top Venues

Publications

Maximilian Wendlinger, Kilian Tscharke, Pascal Debus
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models. CoRR (2024)
Michael Kölle, Afrae Ahouzi, Pascal Debus, Elif Çetiner, Robert Müller, Daniëlle Schuman, Claudia Linnhoff-Popien
Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling. CoRR (2024)
Kilian Tscharke, Sebastian Issel, Pascal Debus
QUACK: Quantum Aligned Centroid Kernel. CoRR (2024)
Sebastian Issel, Kilian Tscharke, Pascal Debus
Towards Classical Software Verification using Quantum Computers. CoRR (2024)
Michael Kölle, Afrae Ahouzi, Pascal Debus, Robert Müller, Daniëlle Schuman, Claudia Linnhoff-Popien
Towards Efficient Quantum Anomaly Detection: One-Class SVMs Using Variable Subsampling and Randomized Measurements. ICAART (2) (2024)
Nicolas M. Müller, Maximilian Burgert, Pascal Debus, Jennifer Williams, Philip Sperl, Konstantin Böttinger
Protecting Publicly Available Data With Machine Learning Shortcuts. CoRR (2023)
Michael Kölle, Afrae Ahouzi, Pascal Debus, Robert Müller, Daniëlle Schuman, Claudia Linnhoff-Popien
Towards Efficient Quantum Anomaly Detection: One-Class SVMs using Variable Subsampling and Randomized Measurements. CoRR (2023)
Nicolas M. Müller, Maximilian Burgert, Pascal Debus, Jennifer Williams, Philip Sperl, Konstantin Böttinger
Protecting Publicly Available Data With Machine Learning Shortcuts. BMVC (2023)
Kilian Tscharke, Sebastian Issel, Pascal Debus
Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel. QCE (2023)
Kilian Tscharke, Sebastian Issel, Pascal Debus
Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel. CoRR (2023)
Karla Markert, Afrae Ahouzi, Pascal Debus
Fairness in Regression - Analysing a Job Candidates Ranking System. GI-Jahrestagung (2022)
Pascal Debus, Nicolas M. Müller, Konstantin Böttinger
Deep Reinforcement Learning for Backup Strategies against Adversaries. CoRR (2021)
Nicolas M. Müller, Daniel Kowatsch, Pascal Debus, Donika Mirdita, Konstantin Böttinger
On GDPR Compliance of Companies' Privacy Policies. TSD (2019)
Nicolas M. Müller, Pascal Debus, Daniel Kowatsch, Konstantin Böttinger
Distributed Anomaly Detection of Single Mote Attacks in RPL Networks. ICETE (2) (2019)