306 citations · 451 across the 18 of their papers we have counts for
11 papers · 1 filter
Discovering Data Encoding Strategies for Quantum-Classical Neural Networks Using Monte Carlo Tree Search
Lena Tokuhiro, Amine Bentellis, Jeanette Miriam Lorenz
Quantum machine learning (QML) has attracted considerable research interest, yet whether it offers practical benefits over classical approaches remains an open question. The choice…
The QuaST Decision Tree: Achieving Automation With Data-Based Recommendations
Benedikt Poggel, Lena Tokuhiro, Georg Kruse +1
Quantum computers are increasingly powerful. Software tools for the development of quantum-enhanced algorithms are maturing. However, the software stack still lacks the connection…
Benchmarking the Variational Quantum Eigensolver using different quantum hardware
Amine Bentellis, Andrea Matic-Flierl, Christian B. Mendl +1
The Variational Quantum Eigensolver (VQE) is a promising quantum algorithm for applications in chemistry within the Noisy Intermediate-Scale Quantum (NISQ) era. The ability for a q…
Pooling techniques in hybrid quantum-classical convolutional neural networks
Maureen Monnet, Hanady Gebran, Andrea Matic-Flierl +4
Quantum machine learning has received significant interest in recent years, with theoretical studies showing that quantum variants of classical machine learning algorithms can prov…
Quantum-Assisted Solution Paths for the Capacitated Vehicle Routing Problem
Lilly Palackal, Benedikt Poggel, Matthias Wulff +3
Many relevant problems in industrial settings result in NP-hard optimization problems, such as the Capacitated Vehicle Routing Problem (CVRP) or its reduced variant, the Travelling…
Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices
Theodora-Augustina Drăgan, Maureen Monnet, Christian B. Mendl +1
Quantum reinforcement learning (QRL) models augment classical reinforcement learning schemes with quantum-enhanced kernels. Different proposals on how to construct such models empi…
Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
Benedikt Poggel, Nils Quetschlich, Lukas Burgholzer +2
Solving real-world optimization problems with quantum computing requires choosing between a large number of options concerning formulation, encoding, algorithm and hardware. Findin…
A Comparative Study On Solving Optimization Problems With Exponentially Fewer Qubits
David Winderl, Nicola Franco, Jeanette Miriam Lorenz
Variational Quantum optimization algorithms, such as the Variational Quantum Eigensolver (VQE) or the Quantum Approximate Optimization Algorithm (QAOA), are among the most studied…
Evaluating the impact of noise on the performance of the Variational Quantum Eigensolver
Marita Oliv, Andrea Matic, Thomas Messerer +1
Quantum computers are expected to be highly beneficial for chemistry simulations, promising significant improvements in accuracy and speed. The most prominent algorithm for chemist…
Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm
Nicola Franco, Tom Wollschlaeger, Nicholas Gao +2
In recent years, quantum computers and algorithms have made significant progress indicating the prospective importance of quantum computing (QC). Especially combinatorial optimizat…
Quantum-classical convolutional neural networks in radiological image classification
Andrea Matic, Maureen Monnet, Jeanette Miriam Lorenz +2
Quantum machine learning is receiving significant attention currently, but its usefulness in comparison to classical machine learning techniques for practical applications remains…