8 papers
QUACOD: Quantum Optimization via Coordinate Descent for Scalable Drone Scheduling
Van-Quang-Huy Nguyen, Hoang-Quan Nguyen, Samee U. Khan +2
Quantum computing has demonstrated its potential to solve various optimization problems, including drone scheduling, which is important not only for drone delivery but also for log…
BRACTIVE: A Brain Activation Approach to Human Visual Brain Learning
Xuan-Bac Nguyen, Hojin Jang, Xin Li +3
The human brain is a highly efficient processing unit, and understanding how it works can inspire new algorithms and architectures in machine learning. In this work, we introduce a…
Quantum-Brain: Quantum-Inspired Neural Network Approach to Vision-Brain Understanding
Hoang-Quan Nguyen, Xuan-Bac Nguyen, Hugh Churchill +4
Vision-brain understanding aims to extract semantic information about brain signals from human perceptions. Existing deep learning methods for vision-brain understanding are usuall…
QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
Hoang-Quan Nguyen, Xuan-Bac Nguyen, Sankalp Pandey +3
Quantum machine learning (QML) has emerged as a promising direction in the noisy intermediate-scale quantum (NISQ) era, offering computational and memory advantages by harnessing s…
QUADRO: A Hybrid Quantum Optimization Framework for Drone Delivery
James B. Holliday, Darren Blount, Hoang Quan Nguyen +2
Quantum computing holds transformative potential for optimizing large-scale drone fleet operations, yet its near-term limitations necessitate hybrid approaches blending classical a…
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Hoang-Quan Nguyen, Xuan Bac Nguyen, Samuel Yen-Chi Chen +4
Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to utilize near-term quantum advantages in multiple problems, including machine learning and comb…