Quantum Computational AI: Algorithms, Systems, and Applications
Editat de Long Cheng, Nishant Saurabh, Ying Maoen Limba Engleză Paperback – 29 sep 2025
- Consolidates key concepts of quantum computing and AI into one accessible resource, bridging the existing knowledge gap
- Provides the latest insights and developments in Quantum Computational AI, offering readers up-to-date information
- Offers practical guidance on applying quantum principles in AI across various real-world sectors, bridging theory and practice
- Aids in skill development for designing, analyzing, and implementing quantum algorithms and systems in AI applications
- Stimulates innovative thinking by providing a thorough understanding of the interdisciplinary field of Quantum Computational AI
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Specificații
ISBN-13: 9780443302596
ISBN-10: 0443302596
Pagini: 304
Dimensiuni: 191 x 235 x 18 mm
Greutate: 0.62 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0443302596
Pagini: 304
Dimensiuni: 191 x 235 x 18 mm
Greutate: 0.62 kg
Editura: ELSEVIER SCIENCE
Cuprins
PART 1 Algorithms
1. Quantum reinforcement learning
2. Exploring quantum federated learning
3. Temporal-spatial quantum graph convolutional neural
network
4. Quantum unsupervised machine learning
PART 2 Systems
5. Distributed learning with quantum-classical collaborative
management
6. Hybrid quantum-classical reinforcement learning for
scheduling systems
7. Efficient full-state simulation for quantum AI systems
8. Machine learning in bosonic quantum systems
PART 3 Applications
9. Quantum support vector machine for power quality analysis
10. Quantum computing for automotive applications
11. Quantum-enhanced decision-making in ACT-R
12. Quantum federated learning for speech emotion
recognition
1. Quantum reinforcement learning
2. Exploring quantum federated learning
3. Temporal-spatial quantum graph convolutional neural
network
4. Quantum unsupervised machine learning
PART 2 Systems
5. Distributed learning with quantum-classical collaborative
management
6. Hybrid quantum-classical reinforcement learning for
scheduling systems
7. Efficient full-state simulation for quantum AI systems
8. Machine learning in bosonic quantum systems
PART 3 Applications
9. Quantum support vector machine for power quality analysis
10. Quantum computing for automotive applications
11. Quantum-enhanced decision-making in ACT-R
12. Quantum federated learning for speech emotion
recognition