| 2025 | ACNS | Protecting Privacy in IoT-Based Deep Learning: State-of-the-Art Methods and Challenges. | Martin Nocker, Florian Merkle, Pascal Schttle, Matthias Janetschek |
| 2025 | DSN | FHE ML Tuxedo: A Tailored Wrapper Architecture for Homomorphic Encryption in Machine Learning. | Martin Nocker, Linus Henke, Pascal Schttle |
| 2025 | ESORICS | Scalable Generation of Invariance-Based Adversarial Examples Using XAI. | Samuel Oberhofer, Martin Nocker, Florian Merkle, Pascal Schttle |
| 2024 | ICPRAM | Incremental Whole Plate ALPR Under Data Availability Constraints. | Markus Russold, Martin Nocker, Pascal Schttle |
| 2024 | VISIGRAPP | Navigating the Trade-Off Between Explainability and Privacy. | Johanna Schmidt, Verena Pietsch, Martin Nocker, Michael Rader, Alessio Montuoro |
| 2023 | EANN | Pruning for Power: Optimizing Energy Efficiency in IoT with Neural Network Pruning. | Thomas Widmann, Florian Merkle, Martin Nocker, Pascal Schttle |
| 2023 | ICIAP | Generating Invariance-Based Adversarial Examples: Bringing Humans Back into the Loop. | Florian Merkle, Mihaela Roxana Sirbu, Martin Nocker, Pascal Schttle |
| 2019 | DAC | Learning Temporal Specifications from Imperfect Traces Using Bayesian Inference. | Artur Mrowca, Martin Nocker, Sebastian Steinhorst, Stephan Gnnemann |