1 citations · 1 across the 4 of their papers we have counts for
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A Fast and Generalizable Fourier Neural Operator-Based Surrogate for Melt-Pool Prediction in Laser Processing
Alix Benoit, Toni Ivas, Mateusz Papierz +3
High-fidelity simulations of laser welding capture complex thermo-fluid phenomena, including phase change, free-surface deformation, and keyhole dynamics, however their computation…
Hybrid quantum recurrent neural network for remaining useful life prediction of turbofan engines
Olga Tsurkan, Aleksandra Konstantinova, Aleksandr Sedykh +5
Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems. We propose a Hybrid Quantum Recurrent Neura…
Photovoltaic power forecasting using quantum machine learning
Asel Sagingalieva, Stefan Komornyik, Arsenii Senokosov +6
Accurate forecasting of photovoltaic power is essential for reliable grid integration, yet remains difficult due to highly variable irradiance, complex meteorological drivers, site…
Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
Alexandr Sedykh, Maninadh Podapaka, Asel Sagingalieva +3
Finding the distribution of the velocities and pressures of a fluid by solving the Navier-Stokes equations is a principal task in the chemical, energy, and pharmaceutical industrie…
Hybrid quantum image classification and federated learning for hepatic steatosis diagnosis
Luca Lusnig, Asel Sagingalieva, Mikhail Surmach +9
In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial. Recognizing the essential need for improved diagnostic precision, particularly fo…