1 citations · 3 across the 5 of their papers we have counts for
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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…