Publications

• Deep Statistical Model Checking, Timo P. Gros, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz, FORTE 2020.
• Components in Probabilistic Systems: Suitable by Construction, Christel Baier, Clemens Dubslaff, Holger Hermanns, Michaela Klauck, Sascha Klüppelholz, Maximilian A. Köhl, ISoLA 2020.
• TraceVis: Towards Visualization for Deep Statistical Model Checking, Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, Marcel Steinmetz, ISoLA 2020.
• Tracking the Race Between Deep Reinforcement Learning and Imitation Learning, Timo P. Gros, Daniel Höller, Jörg Hoffmann, Verena Wolf, QEST 2020.
• Towards Dynamic Dependable Systems Through Evidence-Based Continuous Certification, Rasha Faqeh, Christof Fetzer, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, Maximilian A. Köhl, Marcel Steinmetz, Christoph Weidenbach, ISoLA 2020.
• “Lab Conditions for Research on Explainable Automated Decisions”, Christel Baier, Maria Christakis, Timo P. Gros, David Groß, Stefan Gumhold, Holger Hermanns, Jörg Hoffmann, Michaela Klauck, TAILOR 2020.
• Momba: JANI meets Python, Maximilian A. Köhl, Michaela Klauck, Holger Hermanns, TACAS 2021.
• Automated Safety Verification of Programs Invoking Neural Networks, Maria Christakis, Hasan Ferit Eniser, Holger Hermanns, Jörg Hoffmann, Yugesh Kothari, Jianlin Li, Jorge A. Navas, Valentin Wüstholz, CAV 2021.
• DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning, Timo P. Gros, Daniel Höller, Jörg Hoffmann, Michaela Klauck, Hendrik Meerkamp, Verena Wolf, QEST 2021.