2 citations · 3 across the 10 of their papers we have counts for
11 papers
CORE: Contrast-and-Reflect for Self-Supervised Prompt Optimization in Anomaly Synthesis
Haoxiang Rao, Fang Zhao, Zhao Wang +3
Industrial anomaly detection (AD) is bottlenecked by the scarcity of anomalous samples, making high-fidelity anomaly synthesis crucial for improving downstream performance. However…
Advanced Quantum Annealing for the Bi-Objective Traveling Thief Problem: An -Constraint-based Approach
Nguyen Hoang Viet, Nguyen Xuan Tung, Trinh Van Chien +1
This paper addresses the Bi-Objective Traveling Thief Problem (BI-TTP), a challenging multi-objective optimization problem that requires the simultaneous optimization of travel cos…
Scalable Quantum Message Passing Graph Neural Networks for Next-Generation Wireless Communications: Architectures, Use Cases, and Future Directions
Le Tung Giang, Nguyen Xuan Tung, Trinh Van Chien +2
Graph Neural Networks (GNNs) are eminently suitable for wireless resource management, thanks to their scalability, but they still face computational challenges in large-scale, dens…
D2D Power Allocation via Quantum Graph Neural Network
Tung Giang Le, Xuan Tung Nguyen, Won-Joo Hwang
Increasing wireless network complexity demands scalable resource management. Classical GNNs excel at graph learning but incur high computational costs in large-scale settings. We p…
Vehicle Routing Problems via Quantum Graph Attention Network Deep Reinforcement Learning
Le Tung Giang, Vu Hoang Viet, Nguyen Xuan Tung +2
The vehicle routing problem (VRP) is a fundamental NP-hard task in intelligent transportation systems with broad applications in logistics and distribution. Deep reinforcement lear…
Hybrid Quantum Neural Networks for Efficient Protein-Ligand Binding Affinity Prediction
Seon-Geun Jeong, Kyeong-Hwan Moon, Won-Joo Hwang
Protein-ligand binding affinity is critical in drug discovery, but experimentally determining it is time-consuming and expensive. Artificial intelligence (AI) has been used to pred…
Hybrid Quantum Convolutional Neural Network-Aided Pilot Assignment in Cell-Free Massive MIMO Systems
Doan Hieu Nguyen, Xuan Tung Nguyen, Seon-Geun Jeong +3
A sophisticated hybrid quantum convolutional neural network (HQCNN) is conceived for handling the pilot assignment task in cell-free massive MIMO systems, while maximizing the tota…
Quantum Annealing-Based Sum Rate Maximization for Multi-UAV-Aided Wireless Networks
Seon-Geun Jeong, Pham Dang Anh Duc, Quang Vinh Do +7
In wireless communication networks, it is difficult to solve many NP-hard problems owing to computational complexity and high cost. Recently, quantum annealing (QA) based on quantu…
Graph Neural Networks for Next-Generation-IoT: Recent Advances and Open Challenges
Nguyen Xuan Tung, Le Tung Giang, Bui Duc Son +4
Graph Neural Networks (GNNs) have emerged as a powerful framework for modeling complex interconnected systems, hence making them particularly well-suited to address the growing cha…
Jointly Optimizing Power Allocation and Device Association for Robust IoT Networks under Infeasible Circumstances
Nguyen Xuan Tung, Trinh Van Chien, Dinh Thai Hoang +1
Jointly optimizing power allocation and device association is crucial in Internet-of-Things (IoT) networks to ensure devices achieve their data throughput requirements. Device asso…
Distributed Graph Neural Network Design for Sum Ergodic Spectral Efficiency Maximization in Cell-Free Massive MIMO
Nguyen Xuan Tung, Trinh Van Chien, Hien Quoc Ngo +1
This paper proposes a distributed learning-based framework to tackle the sum ergodic rate maximization problem in cell-free massive multiple-input multiple-output (MIMO) systems by…