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Tensor Networks for Explainable Machine Learning in Cybersecurity
In this paper we show how tensor networks help in developing explainability of machine learning algorithms.
Hacking Cryptographic Protocols with Advanced Variational Quantum Attacks
Our work also shows improvements in attack success rates for lightweight ciphers such as S-DES and S-AES.
Improving Gradient Methods via Coordinate Transformations: Applications to Quantum Machine Learning
In this paper we introduce a generic strategy to accelerate and improve the overall performance of such methods, allowing to alleviate the effect of barren plateaus and local minima.
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