45 citations · 75 across the 9 of their papers we have counts for
5 papers · 1 filter
Tensor networks for quantum computing
Aleksandr Berezutskii, Minzhao Liu, Atithi Acharya +25
In the rapidly evolving field of quantum computing, tensor networks serve as an important tool due to their multifaceted utility. In this paper, we review the diverse applications…
Tensor Quantum Programming
A. Termanova, Ar. Melnikov, E. Mamenchikov +6
Running quantum algorithms often involves implementing complex quantum circuits with such a large number of multi-qubit gates that the challenge of tackling practical applications…
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…
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…
Hybrid quantum ResNet for car classification and its hyperparameter optimization
Asel Sagingalieva, Mo Kordzanganeh, Andrii Kurkin +6
Image recognition is one of the primary applications of machine learning algorithms. Nevertheless, machine learning models used in modern image recognition systems consist of milli…