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Bernhard K. Aichernig

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Edi Muskardin

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Publications

2023
[c102]
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  - conf/fm/PferscherWAM23
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  - https://dblp.org/rec/conf/fm/PferscherWAM23
Andrea Pferscher, Benjamin Wunderling, Bernhard K. Aichernig, Edi Muskardin:
Mining Digital Twins of a VPN Server. FMDT@FM 2023
[c101]
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  - conf/icgi/MuskardinTA23
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Edi Muskardin, Martin Tappler, Bernhard K. Aichernig:
Testing-based Black-box Extraction of Simple Models from RNNs and Transformers. ICGI 2023: 291-294
[c100]
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  - conf/ifm/MuskardinTAP23
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Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Reinforcement Learning Under Partial Observability Guided by Learned Environment Models. iFM 2023: 257-276
[i11]
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  - journals/corr/abs-2306-16854
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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)
[i10]
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  - journals/corr/abs-2306-17204
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Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Bettina Könighofer:
Learning Environment Models with Continuous Stochastic Dynamics. CoRR abs/2306.17204 (2023)
2022
[j23]
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  - journals/isse/MuskardinAPPT22
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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)
[c98]
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Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Martin Tappler:
Learning Finite State Models fromRecurrent Neural Networks. IFM 2022: 229-248
[c93]
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  - journals/corr/abs-2209-14031
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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
[i8]
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  - journals/corr/abs-2206-11708
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Edi Muskardin, Martin Tappler, Bernhard K. Aichernig, Ingo Pill:
Reinforcement Learning under Partial Observability Guided by Learned Environment Models. CoRR abs/2206.11708 (2022)
2021
[c92]
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  - conf/atva/MuskardinAPPT21
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Edi Muskardin, Bernhard K. Aichernig, Ingo Pill, Andrea Pferscher, Martin Tappler:
AALpy: An Active Automata Learning Library. ATVA 2021: 67-73
[c90]
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  - conf/icst/AichernigMP21
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Bernhard K. Aichernig, Edi Muskardin, Andrea Pferscher:
Learning-Based Fuzzing of IoT Message Brokers. ICST 2021: 47-58
[c89]
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  - conf/sefm/TapplerMAP21
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Martin Tappler, Edi Muskardin, Bernhard K. Aichernig, Ingo Pill:
Active Model Learning of Stochastic Reactive Systems. SEFM 2021: 481-500

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