| Learning Bit by Bit: Extracting the Essence of Machine Learning. S Mücke, N Piatkowski, K Morik LWDA, 144-155, 2019 | 19 | 2019 |
| Hardware acceleration of machine learning beyond linear algebra S Mücke, N Piatkowski, K Morik Machine Learning and Knowledge Discovery in Databases: International …, 2020 | 18* | 2020 |
| Quantum Circuit Evolution on NISQ Devices L Franken, B Georgiev, S Mücke, M Wolter, R Heese, C Bauckhage, ... 2022 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2022 | 17* | 2022 |
| Feature selection on quantum computers S Mücke, R Heese, S Müller, M Wolter, N Piatkowski Quantum Machine Intelligence 5 (1), 11, 2023 | 13 | 2023 |
| Yes we care!-certification for machine learning methods through the care label framework KJ Morik, H Kotthaus, R Fischer, S Mücke, M Jakobs, N Piatkowski, ... Frontiers in Artificial Intelligence 5, 975029, 2022 | 13* | 2022 |
| A unified framework for assessing energy efficiency of machine learning R Fischer, M Jakobs, S Mücke, K Morik Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 11 | 2022 |
| Solving Abstract Reasoning Tasks with Grammatical Evolution. R Fischer, M Jakobs, S Mücke, K Morik LWDA, 6-10, 2020 | 11 | 2020 |
| Explaining quantum circuits with shapley values: Towards explainable quantum machine learning R Heese, T Gerlach, S Mücke, S Müller, M Jakobs, N Piatkowski arXiv preprint arXiv:2301.09138, 2023 | 6 | 2023 |
| Optimum-preserving QUBO parameter compression S Mücke, T Gerlach, N Piatkowski arXiv preprint arXiv:2307.02195, 2023 | 3 | 2023 |
| Check Mate: A Sanity Check for Trustworthy AI. S Mücke, L Pfahler LWDA, 91-103, 2022 | 3 | 2022 |
| On the effects of biased quantum random numbers on the initialization of artificial neural networks R Heese, M Wolter, S Mücke, L Franken, N Piatkowski Machine Learning, 1-29, 2024 | 2 | 2024 |
| Shapley Values with Uncertain Value Functions R Heese, S Mücke, M Jakobs, T Gerlach, N Piatkowski International Symposium on Intelligent Data Analysis, 156-168, 2023 | 1 | 2023 |
| Quantum-inspired structure-preserving probabilistic inference S Mücke, N Piatkowski 2022 IEEE Congress on Evolutionary Computation (CEC), 1-9, 2022 | 1 | 2022 |
| Investigating the Relation Between Problem Hardness and QUBO Properties T Gerlach, S Mücke International Symposium on Intelligent Data Analysis, 171-182, 2024 | | 2024 |
| A Simple QUBO Formulation of Sudoku S Mücke arXiv preprint arXiv:2403.04816, 2024 | | 2024 |
| Efficient Light Source Placement using Quantum Computing S Mücke, T Gerlach arXiv preprint arXiv:2312.01156, 2023 | | 2023 |
| Faster QUBO Brute-Force Solving using Gray Code S Mücke arXiv preprint arXiv:2310.19373, 2023 | | 2023 |
| System zur evolutionären Optimierung pseudoboolescher Polynome N Piatkowski, S Mücke | | 2021 |
| Structure Search for Normalizing Flows. F Gonsior, S Mücke, K Morik LWDA, 98-105, 2021 | | 2021 |
| Evolutionäre Optimierung pseudoboolescher Funktionen auf FPGAs S Mücke | | 2019 |
Nico PiatkowskiFraunhofer IAISVerified email at iais.fraunhofer.de
