58 citations · 107 across the 12 of their papers we have counts for
12 papers
QUBOLite: A lightweigth Python toolkit for QUBO
Sascha Mücke, Thore Gerlach, Nico Piatkowski +1
We present QUBOLite, a Python package for the creation, manipulation, analysis, and solution of Quadratic Unconstrained Binary Optimization (QUBO) instances. Built as a thin wrappe…
Kernel -Medoids as General Vector Quantization
Thore Gerlach, Sascha Mücke, Christian Bauckhage
Vector Quantization (VQ) is a widely used technique in machine learning and data compression, valued for its simplicity and interpretability. Among hard VQ methods, -medoids clu…
Predicting Machining Stability with a Quantum Regression Model
Sascha Mücke, Felix Finkeldey, Nico Piatkowski +2
In this article, we propose a novel quantum regression model by extending the Real-Part Quantum SVM. We apply our model to the problem of stability limit prediction in milling proc…
Investigating the Relation Between Problem Hardness and QUBO Properties
Thore Gerlach, Sascha Mücke
Combinatorial optimization problems, integral to various scientific and industrial applications, often vary significantly in their complexity and computational difficulty. Transfor…
A Simple QUBO Formulation of Sudoku
Sascha Mücke
This article describes how to solve Sudoku puzzles using Quadratic Unconstrained Binary Optimization (QUBO). To this end, a QUBO instance with 729 variables is constructed, encodin…
Efficient Light Source Placement using Quantum Computing
Sascha Mücke, Thore Gerlach
NP-hard problems regularly come up in video games, with interesting connections to real-world problems. In the game Minecraft, players place torches on the ground to light up dark…
Faster QUBO Brute-Force Solving using Gray Code
Sascha Mücke
This article describes an improved brute-force solving strategy for Quadratic Unconstrained Binary Optimization (QUBO) problems that is faster than naive approaches and easily para…
Optimum-Preserving QUBO Parameter Compression
Sascha Mücke, Thore Gerlach, Nico Piatkowski
Quadratic unconstrained binary optimization (QUBO) problems are well-studied, not least because they can be approached using contemporary quantum annealing or classical hardware ac…
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning
Raoul Heese, Thore Gerlach, Sascha Mücke +3
Methods of artificial intelligence (AI) and especially machine learning (ML) have been growing ever more complex, and at the same time have more and more impact on people's lives.…
Feature Selection on Quantum Computers
Sascha Mücke, Raoul Heese, Sabine Müller +2
In machine learning, fewer features reduce model complexity. Carefully assessing the influence of each input feature on the model quality is therefore a crucial preprocessing step.…
On the effects of biased quantum random numbers on the initialization of artificial neural networks
Raoul Heese, Moritz Wolter, Sascha Mücke +2
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 interme…
Quantum Circuit Evolution on NISQ Devices
Lukas Franken, Bogdan Georgiev, Sascha Mücke +4
Variational quantum circuits build the foundation for various classes of quantum algorithms. In a nutshell, the weights of a parametrized quantum circuit are varied until the empir…