45 citations · 75 across the 9 of their papers we have counts for
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quant-ph2023
Comparison between Tensor Networks and Variational Quantum Classifier
Georgios Laskaris, Artem A. Melnikov, Michael R. Perelshtein +3
The primary objective of this paper is to conduct a comparative analysis between two Machine Learning approaches: Tensor Networks (TN) and Variational Quantum Classifiers (VQC). Wh…
quant-ph2023★ 10 cited
NISQ-compatible approximate quantum algorithm for unconstrained and constrained discrete optimization
M. R. Perelshtein, A. I. Pakhomchik, Ar. A. Melnikov +7
Quantum algorithms are getting extremely popular due to their potential to significantly outperform classical algorithms. Yet, applying quantum algorithms to optimization problems…