Alexey Melnikov
Alexey Melnikov
Terra Quantum AG, Switzerland
Verified email at - Homepage
Cited by
Cited by
Active learning machine learns to create new quantum experiments
AA Melnikov, HP Nautrup, M Krenn, V Dunjko, M Tiersch, A Zeilinger, ...
Proceedings of the National Academy of Sciences 115 (6), 1221-1226, 2018
Machine learning for long-distance quantum communication
J Wallnöfer, AA Melnikov, W Dür, HJ Briegel
PRX quantum 1 (1), 010301, 2020
Quantum Machine Learning: from physics to software engineering
A Melnikov, M Kordzanganeh, A Alodjants, RK Lee
Advances in Physics: X 8 (1), 2165452, 2023
Dissociation and annihilation of multipartite entanglement structure in dissipative quantum dynamics
SN Filippov, AA Melnikov, M Ziman
Physical Review A 88 (6), 062328, 2013
Projective simulation with generalization
AA Melnikov, A Makmal, V Dunjko, HJ Briegel
Scientific reports 7 (1), 14430, 2017
Predicting quantum advantage by quantum walk with convolutional neural networks
AA Melnikov, LE Fedichkin, A Alodjants
New Journal of Physics 21 (12), 125002, 2019
Quantum walks of interacting fermions on a cycle graph
AA Melnikov, LE Fedichkin
Scientific reports 6 (1), 34226, 2016
Coherent controlization using superconducting qubits
N Friis, AA Melnikov, G Kirchmair, HJ Briegel
Scientific reports 5 (1), 18036, 2015
Setting up experimental Bell tests with reinforcement learning
AA Melnikov, P Sekatski, N Sangouard
Physical Review Letters 125 (16), 160401, 2020
Hybrid quantum ResNet for car classification and its hyperparameter optimization
A Sagingalieva, M Kordzanganeh, A Kurkin, A Melnikov, D Kuhmistrov, ...
Quantum Machine Intelligence 5 (2), 38, 2023
Hybrid quantum neural network for drug response prediction
A Sagingalieva, M Kordzanganeh, N Kenbayev, D Kosichkina, ...
Cancers 15 (10), 2705, 2023
Meta-learning within projective simulation
A Makmal, AA Melnikov, V Dunjko, HJ Briegel
IEEE Access 4, 2110-2122, 2016
Practical application-specific advantage through hybrid quantum computing
M Perelshtein, A Sagingalieva, K Pinto, V Shete, A Pakhomchik, ...
arXiv preprint arXiv:2205.04858, 2022
Quantum machine learning for image classification
A Senokosov, A Sedykh, A Sagingalieva, B Kyriacou, A Melnikov
Machine Learning: Science and Technology 5 (1), 015040, 2024
Projective simulation applied to the grid-world and the mountain-car problem
AA Melnikov, A Makmal, HJ Briegel
arXiv preprint arXiv:1405.5459, 2014
Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms
M Kordzanganeh, M Buchberger, B Kyriacou, M Povolotskii, W Fischer, ...
Advanced Quantum Technologies 6 (8), 2300043, 2023
Machine learning transfer efficiencies for noisy quantum walks
AA Melnikov, LE Fedichkin, RK Lee, A Alodjants
Advanced Quantum Technologies 3 (4), 1900115, 2020
Quantum algorithms applied to satellite mission planning for Earth observation
S Rainjonneau, I Tokarev, S Iudin, S Rayaprolu, K Pinto, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2023
Benchmarking projective simulation in navigation problems
AA Melnikov, A Makmal, HJ Briegel
IEEE Access 6, 64639-64648, 2018
Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
A Sedykh, M Podapaka, A Sagingalieva, K Pinto, M Pflitsch, A Melnikov
Machine Learning: Science and Technology 5 (2), 025045, 2024
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