1 citations · 3 across the 5 of their papers we have counts for
6 papers
Quantum reinforcement learning in dynamic environments
Oliver Sefrin, Manuel Radons, Lars Simon +1
Combining quantum computing techniques in the form of amplitude amplification with classical reinforcement learning has led to the so-called "hybrid agent for quantum-accessible re…
Unsupervised Quantum Anomaly Detection on Noisy Quantum Processors
Daniel Pranjić, Florian Knäble, Philipp Kunst +6
Whether in fundamental physics, cybersecurity or finance, the detection of anomalies with machine learning techniques is a highly relevant and active field of research, as it poten…
Introducing the Kernel Descent Optimizer for Variational Quantum Algorithms
Lars Simon, Holger Eble, Manuel Radons
In recent years, variational quantum algorithms have garnered significant attention as a candidate approach for near-term quantum advantage using noisy intermediate-scale quantum (…
Denoising Gradient Descent in Variational Quantum Algorithms
Lars Simon, Holger Eble, Hagen-Henrik Kowalski +1
In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\e…
Interpolating Parametrized Quantum Circuits using Blackbox Queries
Lars Simon, Holger Eble, Hagen-Henrik Kowalski +1
This article focuses on developing classical surrogates for parametrized quantum circuits using interpolation via (trigonometric) polynomials. We develop two algorithms for the con…
Algorithms for the Training of Neural Support Vector Machines
Lars Simon, Manuel Radons
Neural support vector machines (NSVMs) allow for the incorporation of domain knowledge in the design of the model architecture. In this article we introduce a set of training algor…