Michael Perelshtein

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 9

Top Topics

Machine Learning

Discrete Optimization

Quantum Computing

Classification Rules

Top Venues

Quantum Mach. Intell.

Publications

V. Abronin, A. Naumov, D. Mazur, D. Bystrov, K. Tsarova, Artem Melnikov, Ivan V. Oseledets, Sergey Dolgov, R. Brasher, Michael Perelshtein
TQCompressor: improving tensor decomposition methods in neural networks via permutations. CoRR (2024)
Egor Kornev, Sergey Dolgov, Karan Pinto, Markus Pflitsch, Michael Perelshtein, Artem Melnikov
Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method. CoRR (2023)
Margarita Veshchezerova, Mikhail Somov, David Bertsche, Steffen Limmer, Sebastian Schmitt, Michael Perelshtein, Ayush Joshi Tripathi
A Hybrid Quantum-Classical Approach to the Electric Mobility Problem. QCE (2023)
Asel Sagingalieva, Mohammad Kordzanganeh, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, Michael Perelshtein, Alexey Melnikov, Andrea Skolik, David Von Dollen
Hybrid quantum ResNet for car classification and its hyperparameter optimization. Quantum Mach. Intell. 5 (2) (2023)
A. Naumov, Artem Melnikov, V. Abronin, F. Oxanichenko, K. Izmailov, Markus Pflitsch, A. Melnikov, Michael Perelshtein
Tetra-AML: Automatic Machine Learning via Tensor Networks. CoRR (2023)
Michael Perelshtein, Alexey I. Pakhomchik, Artem Melnikov, M. Podobrii, A. Termanova, I. Kreidich, B. Nuriev, Sergei Iudin, C. W. Mansell, Valerii M. Vinokur
NISQ-compatible approximate quantum algorithm for unconstrained and constrained discrete optimization. Quantum 7 (2023)
Florian Neukart, Anders Indset, Markus Pflitsch, Michael Perelshtein
Do we live in a [quantum] simulation? Constraints, observations, and experiments on the simulation hypothesis. CoRR (2022)
Asel Sagingalieva, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, Michael Perelshtein, Alexey Melnikov, Andrea Skolik, David Von Dollen
Hyperparameter optimization of hybrid quantum neural networks for car classification. CoRR (2022)
Michael Perelshtein, Asel Sagingalieva, Karan Pinto, Vishal Shete, Alexey I. Pakhomchik, Artem Melnikov, Florian Neukart, Georg Gesek, Alexey Melnikov, Valerii M. Vinokur
Practical application-specific advantage through hybrid quantum computing. CoRR (2022)