167 citations · 260 across the 9 of their papers we have counts for
9 papers
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…
On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds
Shubhada Agrawal, Ashwin Ram, Aaditya Ramdas
We present two general lower bounds for stopping times of sequential tests between arbitrary composite nulls and alternatives . The first lower bound is fo…
Predictive control of blast furnace temperature in steelmaking with hybrid depth-infused quantum neural networks
Nayoung Lee, Minsoo Shin, Asel Sagingalieva +5
Accurate prediction and stabilization of blast furnace temperatures are crucial for optimizing the efficiency and productivity of steel production. Traditional methods often strugg…
Multi-stream physics hybrid networks for solving Navier-Stokes equations
Aleksandr Sedykh, Tatjana Protasevich, Mikhail Surmach +4
Understanding and solving fluid dynamics equations efficiently remains a fundamental challenge in computational physics. Traditional numerical solvers and physics-informed neural n…
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 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…
A supervised hybrid quantum machine learning solution to the emergency escape routing problem
Nathan Haboury, Mo Kordzanganeh, Sebastian Schmitt +6
Managing the response to natural disasters effectively can considerably mitigate their devastating impact. This work explores the potential of using supervised hybrid quantum machi…
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…
Quantum machine learning for image classification
Arsenii Senokosov, Alexandr Sedykh, Asel Sagingalieva +2
Image classification, a pivotal task in multiple industries, faces computational challenges due to the burgeoning volume of visual data. This research addresses these challenges by…