| 2025 | LICS | Risk-aware Markov Decision Processes Using Cumulative Prospect Theory. | Thomas Brihaye, Krishnendu Chatterjee, Stefanie Mohr, Maximilian Weininger |
| 2025 | VMCAI | 1-2-3-Go! Policy Synthesis for Parameterized Markov Decision Processes via Decision-Tree Learning and Generalization. | Muqsit Azeem, Debraj Chakraborty, Sudeep Kanav, Jan Kretnsk, MohammadSadegh Mohagheghi, Stefanie Mohr, Maximilian Weininger |
| 2024 | CAV | Monitizer: Automating Design and Evaluation of Neural Network Monitors. | Muqsit Azeem, Marta Grobelna, Sudeep Kanav, Jan Kretnsk, Stefanie Mohr, Sabine Rieder |
| 2024 | TACAS | Learning Explainable and Better Performing Representations of POMDP Strategies. | Alexander Bork, Debraj Chakraborty, Kush Grover, Jan Kretnsk, Stefanie Mohr |
| 2023 | ATVA | Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks. | Calvin Chau, Jan Kretnsk, Stefanie Mohr |
| 2021 | ICMLA | Assessment of Neural Networks for Stream-Water-Temperature Prediction. | Stefanie Mohr, Konstantina Drainas, Jrgen Geist |
| 2021 | RV | Gaussian-Based Runtime Detection of Out-of-distribution Inputs for Neural Networks. | Vahid Hashemi, Jan Kretnsk, Stefanie Mohr, Emmanouil Seferis |
| 2020 | ATVA | DeepAbstract: Neural Network Abstraction for Accelerating Verification. | Pranav Ashok, Vahid Hashemi, Jan Kretnsk, Stefanie Mohr |