1 code implementation • 22 Jan 2023 • Raoul Heese, Thore Gerlach, Sascha Mücke, Sabine Müller, Matthias Jakobs, Nico Piatkowski
The resulting attributions can be interpreted as explanations for why a specific circuit works well for a given task, improving the understanding of how to construct parameterized (or variational) quantum circuits, and fostering their human interpretability in general.
Explainable Artificial Intelligence (XAI) Quantum Machine Learning
no code implementations • 19 Jan 2023 • Raoul Heese, Sascha Mücke, Matthias Jakobs, Thore Gerlach, Nico Piatkowski
We propose a novel definition of Shapley values with uncertain value functions based on first principles using probability theory.
1 code implementation • 24 Mar 2022 • Sascha Mücke, Raoul Heese, Sabine Müller, Moritz Wolter, Nico Piatkowski
In machine learning, fewer features reduce model complexity.
1 code implementation • 30 Aug 2021 • Raoul Heese, Moritz Wolter, Sascha Mücke, Lukas Franken, Nico Piatkowski
Recent advances in practical quantum computing have led to a variety of cloud-based quantum computing platforms that allow researchers to evaluate their algorithms on noisy intermediate-scale quantum (NISQ) devices.
no code implementations • 21 May 2021 • Katharina Morik, Helena Kotthaus, Raphael Fischer, Sascha Mücke, Matthias Jakobs, Nico Piatkowski, Andreas Pauly, Lukas Heppe, Danny Heinrich
How can they be guaranteed for a certain implementation of a machine learning model?
no code implementations • 23 Dec 2020 • Lukas Franken, Bogdan Georgiev, Sascha Mücke, Moritz Wolter, Raoul Heese, Christian Bauckhage, Nico Piatkowski
The results provide intuition on how randomized search heuristics behave on actual quantum hardware and lay out a path for further refinement of evolutionary quantum gate circuits.