Pascal Debus

According to our database, Pascal Debus authored at least 16 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning.

Maximilian Wendlinger, Kilian Tscharke, Pascal Debus

CoRR, July, 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, July, 2025

Quantum Support Vector Regression for Robust Anomaly Detection.

Kilian Tscharke, Maximilian Wendlinger, Sebastian Issel, Pascal Debus

CoRR, May, 2025

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, April, 2025

2024

Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling.

Michael Kölle, Afrae Ahouzi, Pascal Debus, Elif Çetiner, Robert Müller, Daniëlle Schuman, Claudia Linnhoff-Popien

CoRR, 2024

Towards Classical Software Verification using Quantum Computers.

Sebastian Issel, Kilian Tscharke, Pascal Debus

CoRR, 2024

Quantum Machine Learning Playground.

Pascal Debus, Sebastian Issel, Kilian Tscharke

IEEE Computer Graphics and Applications, 2024

A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models.

Maximilian Wendlinger, Kilian Tscharke, Pascal Debus

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

QUACK: Quantum Aligned Centroid Kernel.

Kilian Tscharke, Sebastian Issel, Pascal Debus

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

Towards Efficient Quantum Anomaly Detection: One-Class SVMs Using Variable Subsampling and Randomized Measurements.

Michael Kölle, Afrae Ahouzi, Pascal Debus, Robert Müller, Daniëlle Schuman, Claudia Linnhoff-Popien

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

2023

Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel.

Kilian Tscharke, Sebastian Issel, Pascal Debus

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Protecting Publicly Available Data With Machine Learning Shortcuts.

Nicolas M. Müller, Maximilian Burgert, Pascal Debus, Jennifer Williams, Philip Sperl, Konstantin Böttinger

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Fairness in Regression - Analysing a Job Candidates Ranking System.

Karla Markert, Afrae Ahouzi, Pascal Debus

Proceedings of the 52. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2022, Informatik in den Naturwissenschaften, 26., 2022

2021

Deep Reinforcement Learning for Backup Strategies against Adversaries.

Pascal Debus, Nicolas M. Müller, Konstantin Böttinger

CoRR, 2021

2019

On GDPR Compliance of Companies' Privacy Policies.

Nicolas M. Müller, Daniel Kowatsch, Pascal Debus, Donika Mirdita, Konstantin Böttinger

Proceedings of the Text, Speech, and Dialogue - 22nd International Conference, 2019

Distributed Anomaly Detection of Single Mote Attacks in RPL Networks.

Nicolas M. Müller, Pascal Debus, Daniel Kowatsch, Konstantin Böttinger

Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, 2019