End-to-End Differentiable Architecture: Engineering Synthetic Creativity via Generative Neural Models - Couverture souple
Synopsis
Unlock the future of artificial intelligence with this comprehensive exploration of end-to-end differentiable architectures and their role in engineering synthetic creativity through generative neural models. This authoritative volume delves deep into the mathematical foundations of differentiable programming, offering a robust understanding of the calculus and linear algebra that underpin modern neural networks.
Structured to provide a progressive learning experience, each chapter focuses on a specific concept essential to mastering generative models. Explore automatic differentiation techniques and optimization algorithms tailored for differentiable systems. Gain insights into designing loss functions that foster creativity and examine advanced architectures such as variational autoencoders, generative adversarial networks, transformers, and attention mechanisms.
Discover how normalizing flows enable exact density estimation and how latent space manipulation can produce desired creative outputs. Delve into cutting-edge topics like neural ordinary differential equations, hypernetworks, differentiable physics engines, and differentiable programming languages. The book also addresses the integration of combinatorial optimization, stochastic processes, and reinforcement learning within generative models to enhance their creative capabilities.
Ideal for researchers, practitioners, and advanced students in machine learning and artificial intelligence, this text bridges theory and practice. It equips readers with the knowledge to design and implement sophisticated generative models, leveraging end-to-end differentiability for innovative applications. By presenting detailed explanations, theoretical insights, and practical techniques, this work stands as an indispensable resource for those seeking to push the boundaries of synthetic creativity in AI.
Embark on a journey through the landscape of advanced generative modeling and emerge with the expertise to contribute to this rapidly evolving field. This book is not just a study of current technologies but a gateway to future innovations in the intersection of differentiable programming and artificial creativity.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Résultats de recherche pour End-to-End Differentiable Architecture: Engineering...
Image d'archives
End-to-End Differentiable Architecture (Paperback)
impression à la demandeVendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. Unlock the future of artificial intelligence with this comprehensive exploration of end-to-end differentiable architectures and their role in engineering synthetic creativity through generative neural models. This authoritative volume delves deep into the mathematical foundations of differentiable programming, offering a robust understanding of the calculus and linear algebra that underpin modern neural networks.Structured to provide a progressive learning experience, each chapter focuses on a specific concept essential to mastering generative models. Explore automatic differentiation techniques and optimization algorithms tailored for differentiable systems. Gain insights into designing loss functions that foster creativity and examine advanced architectures such as variational autoencoders, generative adversarial networks, transformers, and attention mechanisms.Discover how normalizing flows enable exact density estimation and how latent space manipulation can produce desired creative outputs. Delve into cutting-edge topics like neural ordinary differential equations, hypernetworks, differentiable physics engines, and differentiable programming languages. The book also addresses the integration of combinatorial optimization, stochastic processes, and reinforcement learning within generative models to enhance their creative capabilities.Ideal for researchers, practitioners, and advanced students in machine learning and artificial intelligence, this text bridges theory and practice. It equips readers with the knowledge to design and implement sophisticated generative models, leveraging end-to-end differentiability for innovative applications. By presenting detailed explanations, theoretical insights, and practical techniques, this work stands as an indispensable resource for those seeking to push the boundaries of synthetic creativity in AI.Embark on a journey through the landscape of advanced generative modeling and emerge with the expertise to contribute to this rapidly evolving field. This book is not just a study of current technologies but a gateway to future innovations in the intersection of differentiable programming and artificial creativity. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798346625766
Acheter neuf
EUR 40,13
Frais de port :
Gratuit
Vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image d'archives
End-to-End Differentiable Architecture
impression à la demandeVendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
PAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9798346625766
Acheter neuf
EUR 40,14
Frais de port :
Gratuit
Vers Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
End-to-End Differentiable Architecture
impression à la demandeVendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L0-9798346625766
Acheter neuf
EUR 37,82
Frais de port :
EUR 4,72
De Royaume-Uni vers Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
End-to-End Differentiable Architecture: Engineering Synthetic Creativity via Generative Neural Models (Mastering Machine Learning)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9798346625766_new
Acheter neuf
EUR 38,09
Frais de port :
EUR 13,59
De Royaume-Uni vers Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
End-to-End Differentiable Architecture (Paperback)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. Unlock the future of artificial intelligence with this comprehensive exploration of end-to-end differentiable architectures and their role in engineering synthetic creativity through generative neural models. This authoritative volume delves deep into the mathematical foundations of differentiable programming, offering a robust understanding of the calculus and linear algebra that underpin modern neural networks.Structured to provide a progressive learning experience, each chapter focuses on a specific concept essential to mastering generative models. Explore automatic differentiation techniques and optimization algorithms tailored for differentiable systems. Gain insights into designing loss functions that foster creativity and examine advanced architectures such as variational autoencoders, generative adversarial networks, transformers, and attention mechanisms.Discover how normalizing flows enable exact density estimation and how latent space manipulation can produce desired creative outputs. Delve into cutting-edge topics like neural ordinary differential equations, hypernetworks, differentiable physics engines, and differentiable programming languages. The book also addresses the integration of combinatorial optimization, stochastic processes, and reinforcement learning within generative models to enhance their creative capabilities.Ideal for researchers, practitioners, and advanced students in machine learning and artificial intelligence, this text bridges theory and practice. It equips readers with the knowledge to design and implement sophisticated generative models, leveraging end-to-end differentiability for innovative applications. By presenting detailed explanations, theoretical insights, and practical techniques, this work stands as an indispensable resource for those seeking to push the boundaries of synthetic creativity in AI.Embark on a journey through the landscape of advanced generative modeling and emerge with the expertise to contribute to this rapidly evolving field. This book is not just a study of current technologies but a gateway to future innovations in the intersection of differentiable programming and artificial creativity. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798346625766
Acheter neuf
EUR 42,63
Frais de port :
EUR 41,97
De Royaume-Uni vers Etats-Unis
Quantité disponible : 1 disponible(s)
Image d'archives
Flux, J: End-to-End Differentiable Architecture
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware - Unlock the future of artificial intelligence with this comprehensive exploration of end-to-end differentiable architectures and their role in engineering synthetic creativity through generative neural models. This authoritative volume delves deep into the mathematical foundations of differentiable programming, offering a robust understanding of the calculus and linear algebra that underpin modern neural networks. N° de réf. du vendeur 9798346625766
Acheter neuf
EUR 54
Frais de port :
EUR 61,45
De Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)