Название: Quantum Generative Adversarial Networks: GANs, Semi-Supervised GANs, Variational Autoencoders
Автор: Pethuru Raj, Jayanthiladevi, Ambika Paranthaman, Amir Masoud Rahmani, Somenath Chakraborty
Издательство: De Gruyter
Год: 2026
Страниц: 389
Язык: английский
Формат: pdf (true), epub
Размер: 54.1 MB
GANs represent a generative model leveraging the growing power of Deep Learning (DL) algorithms. This book presents the breakthroughs, applications and latest research innovations of GANs and of quantum GANs. In particular, the book includes contributions on Autoencoders and Variational Autoencoders, Semi-Supervised GANs, Quantum GANs and Quantum Data Privacy, and Quantum GANs for image manipulation. In recent years, the fusion of Machine learning and quantum computing has transitioned from a niche academic pursuit to a transformative frontier of research and innovation. Among the emerging intersections, Quantum Generative Adversarial Networks (Quantum GANs) stand at the confluence of two revolutionary paradigms: adversarial learning and quantum mechanics. This book, Quantum Generative Adversarial Networks, is both a technical compass and an exploratory guide for readers seeking to understand, implement, and extend the potential of GANs—both classical and quantum—in contemporary and futuristic applications.
Название: Рукоділля
