45 citations · 75 across the 9 of their papers we have counts for
3 papers · 1 filter
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…
Tetra-AML: Automatic Machine Learning via Tensor Networks
A. Naumov, Ar. Melnikov, V. Abronin +5
Neural networks have revolutionized many aspects of society but in the era of huge models with billions of parameters, optimizing and deploying them for commercial applications can…