This book explores the intersection of quantum computing and network science. It bridges the theoretical foundations of quantum walk algorithms with their applications in the structural exploration and representation learning of complex networks.
This book explores the intersection of quantum computing and network science. It bridges the theoretical foundations of quantum walk algorithms with their applications in the structural exploration and representation learning of complex networks.
Fei Yan, PhD, is a professor at the School of Computer Science and Technology, Changchun University of Science and Technology, China. He holds a PhD in Engineering from the Tokyo Institute of Technology, Japan. His research interests include quantum information processing, complex networks, and image processing. Wen Liang, PhD, is an associate professor at the School of Information Science and Engineering, Shenyang Ligong University, China. He holds a PhD in Engineering from the Changchun University of Science and Technology, China. His research interests include complex networks and quantum walks. Fangyan Dong, PhD, is a professor at the Faculty of Mechanical Engineering and Mechanics, Ningbo University, China. She holds a PhD in Engineering from the Tokyo Institute of Technology, Japan. Her research interests include computational intelligence, fuzzy systems, and quantum computing.
Inhaltsangabe
1. Quantum Computing and Quantum Walks 2. Foundational Theory of Quantum Walks 3. Applications of Quantum Walks in Node Discovery 4. Applications of Quantum Walks in Link Mining 5. Applications of Quantum Walks in Community Detection 6. Applications of Quantum Walks in Network Representation Learning 7. Conclusions
1. Quantum Computing and Quantum Walks 2. Foundational Theory of Quantum Walks 3. Applications of Quantum Walks in Node Discovery 4. Applications of Quantum Walks in Link Mining 5. Applications of Quantum Walks in Community Detection 6. Applications of Quantum Walks in Network Representation Learning 7. Conclusions
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