Artem Melnikov

According to our database, Artem Melnikov authored at least 9 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Multi-objective optimization and quantum hybridization of equivariant deep learning interatomic potentials on organic and inorganic compounds.

G. Laskaris, D. Morozov, D. Tarpanov, A. Seth, J. Procelewska, G. Sai Gautam, Asel Sagingalieva, Reuben Brasher, Artem Melnikov

CoRR, February, 2026

2024

TQCompressor: improving tensor decomposition methods in neural networks via permutations.

Vadim Abronin, Aleksei Naumov, Denis Mazur, Dmitriy Bystrov, Katerina Tsarova, Artem Melnikov, Ivan V. Oseledets, Sergey Dolgov, Reuben Brasher, Michael Perelshtein

CoRR, 2024

TQCompressor: Improving Tensor Decomposition Methods in Neural Networks Via Permutations.

Vadim Abronin, Aleksei Naumov, Denis Mazur, Dmitriy Bystrov, Katerina Tsarova, Artem Melnikov, Sergey Dolgov, Reuben Brasher, Michael Perelshtein

Proceedings of the 7th IEEE International Conference on Multimedia Information Processing and Retrieval, 2024

2023

Hybrid quantum ResNet for car classification and its hyperparameter optimization.

Asel Sagingalieva, Mohammad Kordzanganeh, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, Michael Perelshtein, Alexey Melnikov, Andrea Skolik, David Von Dollen

Quantum Mach. Intell., December, 2023

NISQ-compatible approximate quantum algorithm for unconstrained and constrained discrete optimization.

Michael Perelshtein, Alexey I. Pakhomchik, Artem Melnikov, M. Podobrii, A. Termanova, I. Kreidich, B. Nuriev, Sergei Iudin, C. W. Mansell, Valerii M. Vinokur

Quantum, November, 2023

Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method.

Egor Kornev, Sergey Dolgov, Karan Pinto, Markus Pflitsch, Michael Perelshtein, Artem Melnikov

CoRR, 2023

Tetra-AML: Automatic Machine Learning via Tensor Networks.

Aleksei Naumov, Artem Melnikov, Vadim Abronin, F. Oxanichenko, K. Izmailov, Markus Pflitsch, A. Melnikov, Michael Perelshtein

CoRR, 2023

2022

Hyperparameter optimization of hybrid quantum neural networks for car classification.

Asel Sagingalieva, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, Michael Perelshtein, Alexey Melnikov, Andrea Skolik, David Von Dollen

CoRR, 2022

Practical application-specific advantage through hybrid quantum computing.

Michael Perelshtein, Asel Sagingalieva, Karan Pinto, Vishal Shete, Alexey I. Pakhomchik, Artem Melnikov, Florian Neukart, Georg Gesek, Alexey Melnikov, Valerii M. Vinokur

CoRR, 2022