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ORCIDSwantje Plambeck
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2020 – today
- 2024
[c9]Swantje Plambeck
, Aaron Bracht, Nemanja Hranisavljevic, Görschwin Fey:
FaMoS- Fast Model Learning for Hybrid Cyber-Physical Systems using Decision Trees. HSCC 2024: 7:1-7:10- 2023
- [c8]Swantje Plambeck, Görschwin Fey:
Data-Driven Test Generation for Black-Box Systems From Learned Decision Tree Models. DDECS 2023: 27-32 - [c7]Markus Knitt, Swantje Plambeck, Jan Christian Wieck, Julian Kohlisch, Stephan Balduin, Eric M. S. P. Veith, Jakob Schyga, Johannes Hinckeldeyn, Görschwin Fey, Jochen Kreutzfeldt:
Towards the Automatic Generation of Models for Prediction, Monitoring, and Testing of Cyber-Physical Systems. ETFA 2023: 1-4 - 2022
- [c6]Swantje Plambeck, Görschwin Fey:
Regression Trees for System Models and Prediction. OVERLAY@AI*IA 2022: 57-61 - [c5]Swantje Plambeck, Lutz Schammer, Görschwin Fey:
On the Viability of Decision Trees for Learning Models of Systems. ASP-DAC 2022: 696-701 - [c4]Swantje Plambeck, Görschwin Fey:
Decision Tree Models of Continuous Systems. ETFA 2022: 1-8 - [c3]Jakob Schyga, Swantje Plambeck, Johannes Hinckeldeyn, Görschwin Fey, Jochen Kreutzfeldt:
Decision Trees for Analyzing Influences on the Accuracy of Indoor Localization Systems. IPIN 2022: 1-8 - [i2]Jakob Schyga, Swantje Plambeck, Johannes Hinckeldeyn, Görschwin Fey, Jochen Kreutzfeldt:
Decision Trees for Analyzing Influences on the Accuracy of Indoor Localization Systems. CoRR abs/2207.03853 (2022) - 2021
- [c2]Lutz Schammer, Swantje Plambeck, Fin Hendrik Bahnsen, Görschwin Fey:
Learning Models of Cyber-Physical Systems using Automata Learning. COMPSAC 2021: 1224-1229 - [c1]Swantje Plambeck, Gianluca Martino, Görschwin Fey:
Metrics for the Evaluation of Approximate Sequential Streaming Circuits. DSD 2021: 208-211 - [i1]Swantje Plambeck, Jakob Schyga, Johannes Hinckeldeyn, Jochen Kreutzfeldt, Görschwin Fey:
Automata Learning for Automated Test Generation of Real Time Localization Systems. CoRR abs/2105.11911 (2021)
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