Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Kordzanganeh, Mohammad"'
Publikováno v:
Adv. Phys.: X 8(1), 2165452 (2023)
Quantum machine learning is a rapidly growing field at the intersection of quantum technology and artificial intelligence. This review provides a two-fold overview of several key approaches that can offer advancements in both the development of quant
Externí odkaz:
http://arxiv.org/abs/2301.01851
Autor:
Kordzanganeh, Mohammad, Buchberger, Markus, Kyriacou, Basil, Povolotskii, Maxim, Fischer, Wilhelm, Kurkin, Andrii, Somogyi, Wilfrid, Sagingalieva, Asel, Pflitsch, Markus, Melnikov, Alexey
Publikováno v:
Adv. Quantum Technol. 6, 2300043 (2023)
Powerful hardware services and software libraries are vital tools for quickly and affordably designing, testing, and executing quantum algorithms. A robust large-scale study of how the performance of these platforms scales with the number of qubits i
Externí odkaz:
http://arxiv.org/abs/2211.15631
Autor:
Sagingalieva, Asel, Kordzanganeh, Mohammad, Kenbayev, Nurbolat, Kosichkina, Daria, Tomashuk, Tatiana, Melnikov, Alexey
Publikováno v:
Cancers 15(10), 2705 (2023)
Cancer is one of the leading causes of death worldwide. It is caused by a variety of genetic mutations, which makes every instance of the disease unique. Since chemotherapy can have extremely severe side effects, each patient requires a personalized
Externí odkaz:
http://arxiv.org/abs/2211.05777
In this work we introduce a novel approach to the pulsar classification problem in time-domain radio astronomy using a Born machine, often referred to as a quantum neural network. Using a single-qubit architecture, we show that the pulsar classificat
Externí odkaz:
http://arxiv.org/abs/2112.02655
Autor:
Sagingalieva, Asel1 (AUTHOR), Kordzanganeh, Mohammad1 (AUTHOR), Kenbayev, Nurbolat1 (AUTHOR), Kosichkina, Daria1 (AUTHOR), Tomashuk, Tatiana1 (AUTHOR), Melnikov, Alexey1 (AUTHOR) ame@terraquantum.swiss
Publikováno v:
Cancers. May2023, Vol. 15 Issue 10, p2705. 13p.
Akademický článek
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Quantum neural networks represent a new machine learning paradigm that has recently attracted much attention due to its potential promise. Under certain conditions, these models approximate the distribution of their dataset with a truncated Fourier s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d438546c14f4984a2de99c74dae3eb44
http://arxiv.org/abs/2303.03227
http://arxiv.org/abs/2303.03227
Autor:
Rainjonneau, Serge, Tokarev, Igor, Iudin, Sergei, Rayaprolu, Saaketh, Pinto, Karan, Lemtiuzhnikova, Daria, Koblan, Miras, Barashov, Egor, Kordzanganeh, Mohammad, Pflitsch, Markus, Melnikov, Alexey
Earth imaging satellites are a crucial part of our everyday lives that enable global tracking of industrial activities. Use cases span many applications, from weather forecasting to digital maps, carbon footprint tracking, and vegetation monitoring.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8c90f36ea19777e56fa7c1f2a09357e
http://arxiv.org/abs/2302.07181
http://arxiv.org/abs/2302.07181
Autor:
Kordzanganeh, Mohammad, Buchberger, Markus, Kyriacou, Basil, Povolotskii, Maxim, Fischer, Wilhelm, Kurkin, Andrii, Somogyi, Wilfrid, Sagingalieva, Asel, Pflitsch, Markus, Melnikov, Alexey
Publikováno v:
Advanced Quantum Technologies; Aug2023, Vol. 6 Issue 8, p1-1, 1p