|
|
|||
|
||||
OverviewThe scope of the book spans from the fundamental postulates of quantum mechanics and quantum algorithms that underpin QML, to advanced topics including variational quantum algorithms, quantum neural networks, and quantum generative models. It covers both the theoretical formulations, such as expressivity, generalization bounds, and kernel methods, and practical applications, ranging from optimization and pattern recognition to simulation and sensing. The text also explores hybrid quantum-classical workflows, error mitigation strategies, and benchmarks that connect algorithmic development to near-term hardware implementations. By the end of this book, readers gain a holistic view of the current state, promises, and challenges of QML, as well as directions for future research in this rapidly evolving field. Key Features: A chapter on quantum generative models. Accessible reference text useful for both students and researchers. Case studies Full Product DetailsAuthor: Kathleen E Hamilton , Andrea DelgadoPublisher: Institute of Physics Publishing Imprint: Institute of Physics Publishing ISBN: 9780750349536ISBN 10: 0750349530 Pages: 136 Publication Date: 15 December 2025 Audience: General/trade , General Format: Paperback Publisher's Status: Unknown Availability: Available To Order Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
||||