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 003; Valerii M. Vinokur (CoRR, 2022)

Hyperparameter optimization of hybrid quantum neural networks for car classification. - Asel Sagingalieva; Andrii Kurkin; Artem Melnikov; Daniil Kuhmistrov; Michael Perelshtein; Alexey Melnikov 003; Andrea Skolik; David Von Dollen (CoRR, 2022)

Do we live in a [quantum] simulation? Constraints, observations, and experiments on the simulation hypothesis. - Florian Neukart; Anders Indset; Markus Pflitsch; Michael Perelshtein (CoRR, 2022)

A Hybrid Quantum-Classical Approach to the Electric Mobility Problem. - Margarita Veshchezerova; Mikhail Somov; David Bertsche; Steffen Limmer; Sebastian Schmitt; Michael Perelshtein; Ayush Joshi Tripathi (QCE, 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)

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)

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, 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 003; Andrea Skolik; David Von Dollen (Quantum Mach. Intell., 2023)

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 (MIPR, 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)