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2020 – today
- 2024
[j2]Edi Muskardin, Martin Tappler
, Bernhard K. Aichernig, Ingo Pill:
Active model learning of stochastic reactive systems (extended version). Softw. Syst. Model. 23(2): 503-524 (2024)- [c13]Edi Muskardin, Martin Tappler, Ingo Pill, Bernhard K. Aichernig, Thomas Pock:
On the Relationship Between RNN Hidden-State Vectors and Semantic Structures. ACL (Findings) 2024: 5641-5658 - [c12]Edi Muskardin, Tamim Burgstaller, Martin Tappler, Bernhard K. Aichernig:
Active Model Learning of Git Version Control System. ICSTW 2024: 78-82 - [c11]Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Bettina Köninghofer:
Learning Environment Models with Continuous Stochastic Dynamics - with an Application to Deep RL Testing. ICST 2024: 197-208 - 2023
- [c10]Andrea Pferscher, Benjamin Wunderling, Bernhard K. Aichernig, Edi Muskardin:
Mining Digital Twins of a VPN Server. FMDT@FM 2023 - [c9]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig:
Testing-based Black-box Extraction of Simple Models from RNNs and Transformers. ICGI 2023: 291-294 - [c8]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Reinforcement Learning Under Partial Observability Guided by Learned Environment Models. iFM 2023: 257-276 - [i4]Edi Muskardin, Martin Tappler, Ingo Pill, Bernhard K. Aichernig, Thomas Pock:
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth. CoRR abs/2306.16854 (2023) - [i3]Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Bettina Könighofer:
Learning Environment Models with Continuous Stochastic Dynamics. CoRR abs/2306.17204 (2023) - 2022
- [j1]Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Andrea Pferscher, Martin Tappler:
AALpy: an active automata learning library. Innov. Syst. Softw. Eng. 18(3): 417-426 (2022) - [c7]Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Martin Tappler:
Learning Finite State Models fromRecurrent Neural Networks. IFM 2022: 229-248 - [c6]Martin Tappler, Stefan Pranger, Bettina Könighofer, Edi Muskardin, Roderick Bloem, Kim G. Larsen:
Automata Learning Meets Shielding. ISoLA (1) 2022: 335-359 - [c5]Bernhard K. Aichernig, Edi Muskardin, Andrea Pferscher:
Active vs. Passive: A Comparison of Automata Learning Paradigms for Network Protocols. FMAS/ASYDE@SEFM 2022: 1-19 - [i2]Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Reinforcement Learning under Partial Observability Guided by Learned Environment Models. CoRR abs/2206.11708 (2022) - [i1]Martin Tappler, Stefan Pranger, Bettina Könighofer, Edi Muskardin, Roderick Bloem, Kim G. Larsen:
Automata Learning meets Shielding. CoRR abs/2212.01838 (2022) - 2021
- [c4]Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Andrea Pferscher, Martin Tappler:
AALpy: An Active Automata Learning Library. ATVA 2021: 67-73 - [c3]Bernhard K. Aichernig, Edi Muskardin, Andrea Pferscher:
Learning-Based Fuzzing of IoT Message Brokers. ICST 2021: 47-58 - [c2]Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Ingo Pill:
Active Model Learning of Stochastic Reactive Systems. SEFM 2021: 481-500 - 2020
- [c1]Edi Muskardin, Ingo Pill, Franz Wotawa:
CatIO - A Framework for Model-Based Diagnosis of Cyber-Physical Systems. ISMIS 2020: 267-276
Coauthor Index
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