191 citations · 227 across the 13 of their papers we have counts for
14 papers
Towards Transfer Learning for Large-Scale Image Classification Using Annealing-based Quantum Boltzmann Machines
Daniëlle Schuman, Leo Sünkel, Philipp Altmann +4
Quantum Transfer Learning (QTL) recently gained popularity as a hybrid quantum-classical approach for image classification tasks by efficiently combining the feature extraction cap…
Hybrid Quantum Machine Learning Assisted Classification of COVID-19 from Computed Tomography Scans
Leo Sünkel, Darya Martyniuk, Julia J. Reichwald +5
Practical quantum computing (QC) is still in its infancy and problems considered are usually fairly small, especially in quantum machine learning when compared to its classical cou…
SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training
Philipp Altmann, Leo Sünkel, Jonas Stein +3
Applying new computing paradigms like quantum computing to the field of machine learning has recently gained attention. However, as high-dimensional real-world applications are not…
Optimization of QKD Networks with Classical and Quantum Annealing
Bob Godar, Christoph Roch, Jonas Stein +5
This paper analyses a classical and a quantum annealing approach to compute the minimum deployment of Quantum Key Distribution (QKD) hardware in a tier 1 provider network. The ense…
Black Box Optimization Using QUBO and the Cross Entropy Method
Jonas Nüßlein, Christoph Roch, Thomas Gabor +3
Black-box optimization (BBO) can be used to optimize functions whose analytic form is unknown. A common approach to realising BBO is to learn a surrogate model which approximates t…
Towards Multi-Agent Reinforcement Learning using Quantum Boltzmann Machines
Tobias Müller, Christoph Roch, Kyrill Schmid +1
Reinforcement learning has driven impressive advances in machine learning. Simultaneously, quantum-enhanced machine learning algorithms using quantum annealing underlie heavy devel…
A Flexible Pipeline for the Optimization of CSG Trees
Markus Friedrich, Christoph Roch, Sebastian Feld +2
CSG trees are an intuitive, yet powerful technique for the representation of geometry using a combination of Boolean set-operations and geometric primitives. In general, there exis…
The Holy Grail of Quantum Artificial Intelligence: Major Challenges in Accelerating the Machine Learning Pipeline
Thomas Gabor, Leo Sünkel, Fabian Ritz +5
We discuss the synergetic connection between quantum computing and artificial intelligence. After surveying current approaches to quantum artificial intelligence and relating them…
Cross Entropy Hyperparameter Optimization for Constrained Problem Hamiltonians Applied to QAOA
Christoph Roch, Alexander Impertro, Thomy Phan +3
Hybrid quantum-classical algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) are considered as one of the most encouraging approaches for taking advantage of n…
Soccer Team Vectors
Robert Müller, Stefan Langer, Fabian Ritz +3
In this work we present STEVE - Soccer TEam VEctors, a principled approach for learning real valued vectors for soccer teams where similar teams are close to each other in the resu…
Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning
Thomy Phan, Thomas Gabor, Robert Müller +2
We propose Stable Yet Memory Bounded Open-Loop (SYMBOL) planning, a general memory bounded approach to partially observable open-loop planning. SYMBOL maintains an adaptive stack o…
A Quantum Annealing Algorithm for Finding Pure Nash Equilibria in Graphical Games
Christoph Roch, Thomy Phan, Sebastian Feld +3
We introduce Q-Nash, a quantum annealing algorithm for the NP-complete problem of Fnding pure Nash equilibria in graphical games. The algorithm consists of two phases. The first ph…
Assessing Solution Quality of 3SAT on a Quantum Annealing Platform
Thomas Gabor, Sebastian Zielinski, Sebastian Feld +6
When solving propositional logic satisfiability (specifically 3SAT) using quantum annealing, we analyze the effect the difficulty of different instances of the problem has on the q…
A Hybrid Solution Method for the Capacitated Vehicle Routing Problem Using a Quantum Annealer
Sebastian Feld, Christoph Roch, Thomas Gabor +5
The Capacitated Vehicle Routing Problem (CVRP) is an NP-optimization problem (NPO) that has been of great interest for decades for both, science and industry. The CVRP is a variant…