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Raoul Heese
Raoul Heese
Research Fellow at Fraunhofer ITWM
Verified email at itwm.fraunhofer.de
Title
Cited by
Cited by
Year
Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems
L Von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ...
IEEE Transactions on Knowledge and Data Engineering 35 (1), 614-633, 2021
12302021
Challenges and opportunities in quantum optimization
A Abbas, A Ambainis, B Augustino, A Bärtschi, H Buhrman, C Coffrin, ...
Nature Reviews Physics, 1-18, 2024
2652024
Quantum optimization: Potential, challenges, and the path forward
A Abbas, A Ambainis, B Augustino, A Bärtschi, H Buhrman, C Coffrin, ...
arXiv preprint arXiv:2312.02279, 2023
1362023
Feature selection on quantum computers
S Mücke, R Heese, S Müller, M Wolter, N Piatkowski
Quantum Machine Intelligence 5 (1), 11, 2023
692023
Wavelet-packets for deepfake image analysis and detection
M Wolter, F Blanke, R Heese, J Garcke
Machine Learning 111 (11), 4295-4327, 2022
622022
Explaining quantum circuits with shapley values: Towards explainable quantum machine learning
R Heese, T Gerlach, S Mücke, S Müller, M Jakobs, N Piatkowski
Quantum Machine Intelligence 7 (1), 1-33, 2025
372025
Optimized data exploration applied to the simulation of a chemical process
R Heese, M Walczak, T Seidel, N Asprion, M Bortz
Computers & Chemical Engineering 124, 326-342, 2019
272019
Representation of binary classification trees with binary features by quantum circuits
R Heese, P Bickert, AE Niederle
Quantum 6, 676, 2022
262022
Quantum circuit evolution on NISQ devices
L Franken, B Georgiev, S Mucke, M Wolter, R Heese, C Bauckhage, ...
2022 IEEE congress on evolutionary computation (CEC), 1-8, 2022
252022
Quantum optimization: potential, challenges, and the path forward. 2023
A Abbas, A Ambainis, B Augustino, A Bärtschi, H Buhrman, C Coffrin, ...
arXiv preprint arXiv:2312.02279, 2023
242023
Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet simulations with constraints
PO Ludl, R Heese, J Höller, N Asprion, M Bortz
Frontiers of Chemical Science and Engineering 16 (2), 183-197, 2022
222022
An optimization case study for solving a transport robot scheduling problem on quantum-hybrid and quantum-inspired hardware
D Leib, T Seidel, S Jäger, R Heese, C Jones, A Awasthi, A Niederle, ...
Scientific Reports 13 (1), 18743, 2023
192023
Quantum Optimization Benchmark Library--The Intractable Decathlon
T Koch, DEB Neira, Y Chen, G Cortiana, DJ Egger, R Heese, NN Hegade, ...
arXiv preprint arXiv:2504.03832, 2025
182025
Informed machine learning-a taxonomy and survey of integrating knowledge into learning systems. arXiv
L Von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ...
Machine Learning, 2019
172019
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 113 (3), 1189-1217, 2024
152024
Quantum computing for discrete optimization: A highlight of three technologies
A Bochkarev, R Heese, S Jäger, P Schiewe, A Schöbel
European Journal of Operational Research, 2025
142025
The good, the bad and the ugly: Augmenting a black-box model with expert knowledge
R Heese, M Walczak, L Morand, D Helm, M Bortz
International Conference on Artificial Neural Networks, 391-395, 2019
142019
Gradient-free quantum optimization on NISQ devices
L Franken, B Georgiev, S Muecke, M Wolter, N Piatkowski, C Bauckhage
arXiv preprint arXiv:2012.13453, 2020
122020
Multiplicities in thermodynamic activity coefficients
J Werner, T Seidel, R Jafar, R Heese, H Hasse, M Bortz
AIChE Journal 69 (12), e18251, 2023
92023
The big picture of neurodegeneration: a meta study to extract the essential evidence on neurodegenerative diseases in a network-based approach
N Ruffini, S Klingenberg, R Heese, S Schweiger, S Gerber
Frontiers in aging neuroscience 14, 866886, 2022
82022
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Articles 1–20