13 citations · 33 across the 13 of their papers we have counts for
13 papers
From Classical Data to Quantum Advantage -- Quantum Policy Evaluation on Quantum Hardware
Daniel Hein, Simon Wiedemann, Markus Baumann +7
Quantum policy evaluation (QPE) is a reinforcement learning (RL) algorithm which is quadratically more efficient than an analogous classical Monte Carlo estimation. It makes use of…
Quantum Boltzmann Machines using Parallel Annealing for Medical Image Classification
Daniëlle Schuman, Mark V. Seebode, Tobias Rohe +5
Exploiting the fact that samples drawn from a quantum annealer inherently follow a Boltzmann-like distribution, annealing-based Quantum Boltzmann Machines (QBMs) have gained increa…
Reducing QUBO Density by Factoring Out Semi-Symmetries
Jonas Nüßlein, Leo Sünkel, Jonas Stein +6
Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are prominent approaches for solving combinatorial optimization problems, such as those formulated as Quadra…
Reducing QAOA Circuit Depth by Factoring out Semi-Symmetries
Jonas Nüßlein, Leo Sünkel, Jonas Stein +4
QAOA is a quantum algorithm for solving combinatorial optimization problems. It is capable of searching for the minimizing solution vector of a QUBO problem . The number…
Towards Less Greedy Quantum Coalition Structure Generation in Induced Subgraph Games
Jonas Nüßlein, Daniëlle Schuman, David Bucher +5
The transition to 100% renewable energy requires new techniques for managing energy networks, such as dividing them into sensible subsets of prosumers called micro-grids. Doing so…
Efficient Quantum One-Class Support Vector Machines for Anomaly Detection Using Randomized Measurements and Variable Subsampling
Michael Kölle, Afrae Ahouzi, Pascal Debus +4
Quantum one-class support vector machines leverage the advantage of quantum kernel methods for semi-supervised anomaly detection. However, their quadratic time complexity with resp…
The Questionable Influence of Entanglement in Quantum Optimisation Algorithms
Tobias Rohe, Daniëlle Schuman, Jonas Nüßlein +3
The performance of the Variational Quantum Eigensolver (VQE) is promising compared to other quantum algorithms, but also depends significantly on the appropriate design of the unde…
Sampling Problems on a Quantum Computer
Maximilian Balthasar Mansky, Jonas Nüßlein, David Bucher +3
Due to the advances in the manufacturing of quantum hardware in the recent years, significant research efforts have been directed towards employing quantum methods to solving probl…
Towards Efficient Quantum Anomaly Detection: One-Class SVMs using Variable Subsampling and Randomized Measurements
Michael Kölle, Afrae Ahouzi, Pascal Debus +3
Quantum computing, with its potential to enhance various machine learning tasks, allows significant advancements in kernel calculation and model precision. Utilizing the one-class…
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…
Benchmarking Quantum Surrogate Models on Scarce and Noisy Data
Jonas Stein, Michael Poppel, Philip Adamczyk +9
Surrogate models are ubiquitously used in industry and academia to efficiently approximate given black box functions. As state-of-the-art methods from classical machine learning fr…
Exploring Unsupervised Anomaly Detection with Quantum Boltzmann Machines in Fraud Detection
Jonas Stein, Daniëlle Schuman, Magdalena Benkard +7
Anomaly detection in Endpoint Detection and Response (EDR) is a critical task in cybersecurity programs of large companies. With rapidly growing amounts of data and the omnipresenc…
Solving Large Steiner Tree Problems in Graphs for Cost-Efficient Fiber-To-The-Home Network Expansion
Tobias Müller, Kyrill Schmid, Daniëlle Schuman +3
The expansion of Fiber-To-The-Home (FTTH) networks creates high costs due to expensive excavation procedures. Optimizing the planning process and minimizing the cost of the earth e…