Quantum Generative Adversarial Networks by Pethuru Raj (.ePUB)+
File Size: 54.1 MB
Quantum Generative Adversarial Networks: GANs, Semi-Supervised GANs, Variational Autoencoders by Pethuru Raj, Jayanthiladevi, Ambika Paranthaman, Amir Masoud Rahmani, Somenath Chakraborty
Requirements: .ePUB, .PDF reader, 54.1 MB | True PDF, True EPUB
Overview: 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. This book is intended for researchers, developers, entrepreneurs, and students who aspire to contribute to or understand the evolving landscape of adversarial networks and their quantum counterparts.
Genre: Non-Fiction > Tech & Devices
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