most citedQuantum Machine Learning: from physics to software engineering

99 citations · 279 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023★ 10 cited

Forecasting steam mass flow in power plants using the parallel hybrid network

Andrii Kurkin, Jonas Hegemann, Mo Kordzanganeh +1

Efficient and sustainable power generation is a crucial concern in the energy sector. In particular, thermal power plants grapple with accurately predicting steam mass flow, which…

quant-ph2023★ 28 cited

Parallel Hybrid Networks: an interplay between quantum and classical neural networks

Mo Kordzanganeh, Daria Kosichkina, Alexey Melnikov

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 ap…

quant-ph2023★ 64 cited

Quantum algorithms applied to satellite mission planning for Earth observation

Serge Rainjonneau, Igor Tokarev, Sergei Iudin +8

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 t…

quant-ph2023★ 99 cited

Quantum Machine Learning: from physics to software engineering

Alexey Melnikov, Mohammad Kordzanganeh, Alexander Alodjants +1

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 a…

quant-ph2022★ 18 cited

An exponentially-growing family of universal quantum circuits

Mo Kordzanganeh, Pavel Sekatski, Leonid Fedichkin +1

Quantum machine learning has become an area of growing interest but has certain theoretical and hardware-specific limitations. Notably, the problem of vanishing gradients, or barre…

quant-ph2022★ 47 cited

Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms

Mohammad Kordzanganeh, Markus Buchberger, Basil Kyriacou +7

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…

quant-ph2022★ 13 cited

Automated design of quantum optical experiments for device-independent quantum key distribution

Xavier Valcarce, Pavel Sekatski, Elie Gouzien +2

Device-independent quantum key distribution (DIQKD) reduces the vulnerability to side-channel attacks of standard QKD protocols by removing the need for characterized quantum devic…