publications

a list of my scientific papers.

2025

  1. Explaining quantum circuits with Shapley values: towards explainable quantum machine learning
    Raoul Heese, Thore Gerlach, Sascha Mücke, and 3 more authors
    Quantum Machine Intelligence, 2025
    BIB 
    @article{heese.etal.2025a,
  author = {Heese, Raoul and Gerlach, Thore and M{\"u}cke, Sascha and M{\"u}ller, Sabine and Jakobs, Matthias and Piatkowski, Nico},
  title = {Explaining quantum circuits with Shapley values: towards explainable quantum machine learning},
  journal = {Quantum Machine Intelligence},
  year = {2025},
  volume = {7},
  number = {1},
  pages = {27},
  doi = {10.1007/s42484-025-00254-8},
  website = {https://link.springer.com/article/10.1007/s42484-025-00254-8},
  selected = {true}
}
    Paper
  2. Optimum-Preserving QUBO Parameter Compression
    Sascha Mücke, Thore Gerlach, and Nico Piatkowski
    Quantum Machine Intelligence, 2025
    BIB 
    @article{muecke.etal.2024a,
  title = {Optimum-Preserving {QUBO} {Parameter} {Compression}},
  author = {M{\"u}cke, Sascha and Gerlach, Thore and Piatkowski, Nico},
  year = {2025},
  journal = {Quantum Machine Intelligence},
  volume = {7},
  doi = {10.1007/s42484-024-00219-3},
  website = {https://link.springer.com/article/10.1007/s42484-024-00219-3},
  selected = {true}
}
    Paper
  3. Quantum-Classical Optimization in Machine Learning
    Sascha Mücke
    Jul 2025
    BIB 
    @book{muecke.2025a,
  author = {M{\"{u}}cke, Sascha},
  title = {Quantum-Classical Optimization in Machine Learning},
  series = {Schriftenreihe Virtual Machining},
  volume = {8},
  publisher = {Shaker Verlag},
  year = {2025},
  month = jul,
  address = {D{\"{u}}ren},
  isbn = {9783819101342},
  pdf = {dissertation_muecke_final.pdf},
  selected = {true}
}
    PDF

2024

  1. On the effects of biased quantum random numbers on the initialization of artificial neural networks
    Raoul Heese, Moritz Wolter, Sascha Mücke, and 2 more authors
    Machine Learning, Jul 2024
    BIB 
    @article{heese2024effects,
  title = {On the effects of biased quantum random numbers on the initialization of artificial neural networks},
  author = {Heese, Raoul and Wolter, Moritz and M{\"u}cke, Sascha and Franken, Lukas and Piatkowski, Nico},
  journal = {Machine Learning},
  pages = {1--29},
  year = {2024},
  publisher = {Springer},
  website = {https://link.springer.com/article/10.1007/s10994-023-06490-y},
  selected = {true}
}
    Paper
  2. Investigating the Relation Between Problem Hardness and QUBO Properties
    Thore Gerlach, and Sascha Mücke
    In International Symposium on Intelligent Data Analysis, Jul 2024
    BIB 
    @inproceedings{gerlach2024investigating,
  title = {Investigating the Relation Between Problem Hardness and QUBO Properties},
  author = {Gerlach, Thore and M{\"u}cke, Sascha},
  booktitle = {International Symposium on Intelligent Data Analysis},
  pages = {171--182},
  year = {2024},
  organization = {Springer},
  website = {https://link.springer.com/chapter/10.1007/978-3-031-58553-1_14}
}
    Paper
  3. A Simple QUBO Formulation of Sudoku
    Sascha Mücke
    In Companion Proceedings of the Genetic and Evolutionary Computation Conference, Jul 2024
    BIB 
    @inproceedings{muecke.2024a,
  title = {A Simple {QUBO} Formulation of Sudoku},
  author = {M{\"{u}}cke, Sascha},
  year = {2024},
  booktitle = {Companion Proceedings of the Genetic and Evolutionary Computation Conference},
  publisher = {{ACM}},
  pages = {1958--1962},
  doi = {10.1145/3638530.3664106},
  website = {https://dl.acm.org/doi/10.1145/3638530.3664106},
  selected = {true}
}
    Paper
  4. Real-Part Quantum Support Vector Machines
    Nico Piatkowski, and Sascha Mücke
    In Proceedings of Machine Learning and Knowledge Discovery in Databases, Jul 2024
    BIB 
    @inproceedings{piatkowski.muecke.2024a,
  title = {Real-Part Quantum Support Vector Machines},
  author = {Piatkowski, Nico and M{\"{u}}cke, Sascha},
  year = {2024},
  booktitle = {Proceedings of Machine Learning and Knowledge Discovery in Databases},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  volume = {14948},
  pages = {144--160},
  doi = {10.1007/978-3-031-70371-3_9},
  website = {https://link.springer.com/chapter/10.1007/978-3-031-70371-3_9}
}
    Paper
  5. Predicting Machining Stability with a Quantum Regression Model
    Sascha Mücke, Felix Finkeldey, Nico Piatkowski, and 2 more authors
    Jul 2024
    BIB 
    @misc{muecke.etal.2024b,
  title = {Predicting Machining Stability with a Quantum Regression Model},
  author = {M\"{u}cke, Sascha and Finkeldey, Felix and Piatkowski, Nico and Siebrecht, Tobias and Wiederkehr, Petra},
  year = {2024},
  url = {https://arxiv.org/abs/2412.04048},
  eprint = {2412.04048},
  archiveprefix = {arXiv},
  primaryclass = {quant-ph}
}

2023

  1. A Unified Framework for Assessing Energy Efficiency of Machine Learning
    Raphael Fischer, Matthias Jakobs, Sascha Mücke, and 1 more author
    In Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part I, Jul 2023
    BIB 
    @inproceedings{fischer2023,
  title = {A Unified Framework for Assessing Energy Efficiency of Machine Learning},
  booktitle = {Machine Learning and Principles and Practice of Knowledge Discovery in Databases: {{International}} Workshops of {{ECML PKDD}} 2022, Grenoble, France, September 19\textendash 23, 2022, Proceedings, Part {{I}}},
  author = {Fischer, Raphael and Jakobs, Matthias and M{\"u}cke, Sascha and Morik, Katharina},
  year = {2023},
  pages = {39--54},
  organization = {{Springer}}
}
  2. Shapley Values with Uncertain Value Functions
    Raoul Heese, Sascha Mücke, Matthias Jakobs, and 2 more authors
    In International Symposium on Intelligent Data Analysis, Jul 2023
    BIB 
    @inproceedings{heese2023shapley,
  title = {Shapley Values with Uncertain Value Functions},
  author = {Heese, Raoul and M{\"u}cke, Sascha and Jakobs, Matthias and Gerlach, Thore and Piatkowski, Nico},
  booktitle = {International Symposium on Intelligent Data Analysis},
  pages = {156--168},
  year = {2023},
  organization = {Springer Nature Switzerland Cham},
  selected = {true}
}
  3. Explainable Quantum Machine Learning
    Raoul Heese, Thore Gerlach, Sascha Mücke, and 3 more authors
    arXiv preprint arXiv:2301.09138, Jul 2023
    BIB 
    @article{heese2023a,
  title = {Explainable Quantum Machine Learning},
  author = {Heese, Raoul and Gerlach, Thore and M{\"u}cke, Sascha and M{\"u}ller, Sabine and Jakobs, Matthias and Piatkowski, Nico},
  year = {2023},
  journal = {arXiv preprint arXiv:2301.09138},
  eprint = {2301.09138},
  archiveprefix = {arxiv}
}
  4. Feature Selection on Quantum Computers
    Sascha Mücke, Raoul Heese, Sabine Müller, and 2 more authors
    Quantum Machine Intelligence, Jul 2023
    BIB 
    @article{mucke2023,
  title = {Feature Selection on Quantum Computers},
  author = {M{\"u}cke, Sascha and Heese, Raoul and M{\"u}ller, Sabine and Wolter, Moritz and Piatkowski, Nico},
  year = {2023},
  journal = {Quantum Machine Intelligence},
  volume = {5},
  number = {1},
  website = {https://link.springer.com/article/10.1007/s42484-023-00099-z},
  selected = {true}
}
    Paper
  5. Efficient Light Source Placement using Quantum Computing
    Sascha Mücke, and Thore Gerlach
    In Lernen, Wissen, Daten, Analysen, Jul 2023
    BIB 
    @inproceedings{muecke.gerlach.2023a,
  title = {Efficient Light Source Placement using Quantum Computing},
  author = {M{\"{u}}cke, Sascha and Gerlach, Thore},
  year = {2023},
  booktitle = {Lernen, Wissen, Daten, Analysen},
  publisher = {CEUR-WS.org},
  series = {{CEUR} Workshop Proceedings},
  volume = {3630},
  pages = {478--491},
  pdf = {https://ceur-ws.org/Vol-3630/LWDA2023-paper42.pdf},
  selected = {true}
}
    PDF

2022

  1. Quantum Circuit Evolution on NISQ Devices
    Lukas Franken, Bogdan Georgiev, Sascha Mücke, and 4 more authors
    In 2022 IEEE Congress on Evolutionary Computation (CEC), Jul 2022
    BIB 
    @inproceedings{franken2022,
  title = {Quantum Circuit Evolution on {{NISQ}} Devices},
  booktitle = {2022 {{IEEE}} Congress on Evolutionary Computation ({{CEC}})},
  author = {Franken, Lukas and Georgiev, Bogdan and M{\"u}cke, Sascha and Wolter, Moritz and Heese, Raoul and Bauckhage, Christian and Piatkowski, Nico},
  year = {2022},
  pages = {1--8},
  selected = {true}
}
  2. Yes We Care!-Certification for Machine Learning Methods through the Care Label Framework
    Katharina J. Morik, Helena Kotthaus, Raphael Fischer, and 6 more authors
    Frontiers in Artificial Intelligence, Jul 2022
    BIB 
    @article{morik2022,
  title = {Yes We Care!-{{Certification}} for Machine Learning Methods through the Care Label Framework},
  author = {Morik, Katharina J. and Kotthaus, Helena and Fischer, Raphael and M{\"u}cke, Sascha and Jakobs, Matthias and Piatkowski, Nico and Pauly, Andreas and Heppe, Lukas and Heinrich, Danny},
  year = {2022},
  journal = {Frontiers in Artificial Intelligence},
  volume = {5}
}
  3. Quantum-Inspired Structure-Preserving Probabilistic Inference
    Sascha Mücke, and Nico Piatkowski
    In 2022 IEEE Congress on Evolutionary Computation (CEC), Jul 2022
    BIB 
    @inproceedings{mucke2022,
  title = {Quantum-Inspired Structure-Preserving Probabilistic Inference},
  booktitle = {2022 {{IEEE}} Congress on Evolutionary Computation ({{CEC}})},
  author = {M{\"u}cke, Sascha and Piatkowski, Nico},
  year = {2022},
  pages = {1--9},
  organization = {{IEEE}}
}
  4. Check Mate: A Sanity Check for Trustworthy AI
    Sascha Mücke, and Lukas Pfahler
    In Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen" (LWDA), Jul 2022
    BIB 
    @inproceedings{mucke2022a,
  title = {Check {{Mate}}: {{A Sanity Check}} for {{Trustworthy AI}}},
  booktitle = {Proceedings of the {{Conference}} on "{{Lernen}}, {{Wissen}}, {{Daten}}, {{Analysen}}" ({{LWDA}})},
  author = {M{\"u}cke, Sascha and Pfahler, Lukas},
  year = {2022},
  volume = {3341},
  pages = {91--103}
}

2021

  1. Structure Search for Normalizing Flows
    Felix Gonsior, Sascha Mücke, and Katharina Morik
    In Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen" (LWDA), Jul 2021
    BIB 
    @inproceedings{gonsior2021,
  title = {Structure Search for Normalizing Flows},
  booktitle = {Proceedings of the {{Conference}} on "{{Lernen}}, {{Wissen}}, {{Daten}}, {{Analysen}}" ({{LWDA}})},
  author = {Gonsior, Felix and M{\"u}cke, Sascha and Morik, Katharina},
  year = {2021},
  volume = {2993},
  pages = {98--105}
}

2020

  1. Solving Abstract Reasoning Tasks with Grammatical Evolution.
    Raphael Fischer, Matthias Jakobs, Sascha Mücke, and 1 more author
    In LWDA, Jul 2020
    BIB 
    @inproceedings{fischer2020,
  title = {Solving Abstract Reasoning Tasks with Grammatical Evolution.},
  booktitle = {{{LWDA}}},
  author = {Fischer, Raphael and Jakobs, Matthias and M{\"u}cke, Sascha and Morik, Katharina},
  year = {2020},
  pages = {6--10}
}

2019

  1. Hardware Accelerated Learning at the Edge
    Sascha Mücke, Nico Piatkowski, and Katharina Morik
    In Decentralized Machine Learning at the Edge, Jul 2019
    BIB 
    @inproceedings{mucke2019,
  title = {Hardware {{Accelerated Learning}} at the {{Edge}}},
  booktitle = {Decentralized {{Machine Learning}} at the {{Edge}}},
  author = {M{\"u}cke, Sascha and Piatkowski, Nico and Morik, Katharina},
  year = {2019},
  publisher = {{Springer}}
}
  2. Learning Bit by Bit: Extracting the Essence of Machine Learning
    Sascha Mücke, Nico Piatkowski, and Katharina Morik
    In Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen" (LWDA), Jul 2019
    BIB 
    @inproceedings{mucke2019a,
  title = {Learning {{Bit}} by {{Bit}}: {{Extracting}} the {{Essence}} of {{Machine Learning}}},
  booktitle = {Proceedings of the {{Conference}} on "{{Lernen}}, {{Wissen}}, {{Daten}}, {{Analysen}}" ({{LWDA}})},
  author = {M{\"u}cke, Sascha and Piatkowski, Nico and Morik, Katharina},
  year = {2019},
  series = {{{CEUR Workshop Proceedings}}},
  volume = {2454},
  pages = {144--155}
}
  3. Evolutionäre Optimierung Pseudoboolescher Funktionen Auf FPGAs
    Sascha Mücke
    TU Dortmund University, Jul 2019
    BIB 
    @mastersthesis{muckeEvolutionareOptimierungPseudoboolescher2019,
  title = {Evolution\"are {{Optimierung}} Pseudoboolescher {{Funktionen}} Auf {{FPGAs}}},
  author = {M{\"u}cke, Sascha},
  year = {2019},
  school = {TU Dortmund University},
  pdf = {https://www-ai.cs.tu-dortmund.de/PublicPublicationFiles/muecke_2019a.pdf}
}
    PDF