18 citations · 52 across the 12 of their papers we have counts for
7 papers · 2 filters
Certifiably Robust Encoding Schemes
Aman Saxena, Tom Wollschläger, Nicola Franco +2
Quantum machine learning uses principles from quantum mechanics to process data, offering potential advances in speed and performance. However, previous work has shown that these m…
Identifying Bottlenecks of NISQ-friendly HHL algorithms
Marc Andreu Marfany, Alona Sakhnenko, Jeanette Miriam Lorenz
Quantum computing promises enabling solving large problem instances, e.g. large linear equation systems with HHL algorithm, once the hardware stack matures. For the foreseeable fut…
Quadratic Advantage with Quantum Randomized Smoothing Applied to Time-Series Analysis
Nicola Franco, Marie Kempkes, Jakob Spiegelberg +1
As quantum machine learning continues to develop at a rapid pace, the importance of ensuring the robustness and efficiency of quantum algorithms cannot be overstated. Our research…
Building Continuous Quantum-Classical Bayesian Neural Networks for a Classical Clinical Dataset
Alona Sakhnenko, Julian Sikora, Jeanette Miriam Lorenz
In this work, we are introducing a Quantum-Classical Bayesian Neural Network (QCBNN) that is capable to perform uncertainty-aware classification of classical medical dataset. This…
Constructing Optimal Noise Channels for Enhanced Robustness in Quantum Machine Learning
David Winderl, Nicola Franco, Jeanette Miriam Lorenz
With the rapid advancement of Quantum Machine Learning (QML), the critical need to enhance security measures against adversarial attacks and protect QML models becomes increasingly…
Benchmarking Quantum Generative Learning: A Study on Scalability and Noise Resilience using QUARK
Florian J. Kiwit, Maximilian A. Wolf, Marwa Marso +4
Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to…
Predominant Aspects on Security for Quantum Machine Learning: Literature Review
Nicola Franco, Alona Sakhnenko, Leon Stolpmann +4
Quantum Machine Learning (QML) has emerged as a promising intersection of quantum computing and classical machine learning, anticipated to drive breakthroughs in computational task…