Generative Adversarial Learning: Architectures and Applications, Razavi-Far Roozbeh, Ruiz-Garcia Ariel, Palade Vasile
Автор: Mao Xudong, Li Qing Название: Generative Adversarial Networks for Image Generation ISBN: 981336047X ISBN-13(EAN): 9789813360471 Издательство: Springer Цена: 139750.00 T Наличие на складе: Поставка под заказ. Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
Автор: Tomczak Jakub M. Название: Deep Generative Modeling ISBN: 3030931579 ISBN-13(EAN): 9783030931575 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Поставка под заказ. Описание: This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions. Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github. The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.
Автор: Hany John, Walters Greg Название: Hands-On Generative Adversarial Networks with PyTorch 1.x ISBN: 1789530512 ISBN-13(EAN): 9781789530513 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book will help you understand how GANs architecture works using PyTorch. You will get familiar with the most flexible deep learning toolkit and use it to transform ideas into actual working codes. You will apply GAN models to areas like computer vision, multimedia and natural language processing using a sample-generation perspective.
Автор: Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, J. D. Tygar Название: Adversarial Machine Learning ISBN: 1107043468 ISBN-13(EAN): 9781107043466 Издательство: Cambridge Academ Рейтинг: Цена: 83430.00 T Наличие на складе: Невозможна поставка. Описание: Combining essential theory and practical techniques for analysing system security, and building robust machine learning in adversarial environments, as well as including case studies on email spam and network security, this complete introduction is an invaluable resource for researchers, practitioners and students in computer security and machine learning.
Автор: Babcock Joseph, Bali Raghav Название: Generative AI with Python and TensorFlow 2: Harness the power of generative models to create images, text, and music ISBN: 1800200889 ISBN-13(EAN): 9781800200883 Издательство: Неизвестно Рейтинг: Цена: 80910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Packed with intriguing real-world projects as well as theory, Generative AI with Python and TensorFlow 2 enables you to leverage artificial intelligence creatively and generate human-like data in the form of speech, text, images, and music.
Автор: Valle Rafael Название: Hands-On Generative Adversarial Networks with Keras ISBN: 1789538203 ISBN-13(EAN): 9781789538205 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book will explore deep learning and generative models, and their applications in artificial intelligence. You will learn to evaluate and improve your GAN models by eliminating challenges that are encountered in real-world applications. You will implement GAN architectures in various domains such as computer vision, NLP, and audio processing
Автор: Yevgeniy Vorobeychik, Murat Kantarcioglu Название: Adversarial Machine Learning ISBN: 1681733978 ISBN-13(EAN): 9781681733975 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 91470.00 T Наличие на складе: Невозможна поставка. Описание: Recounts the thrilling tale of America`s first spy drama - the legendary Frank Wisner`s intelligence operations in Romania as World War II ended and the Cold War dawned. Painstakingly reconstructed with the aid of specialised literature and archival collections, the story that emerges is one of danger and stealth, a real-life spy thriller unfolding just as the Cold War began.
Автор: Engelhardt Sandy, Oksuz Ilkay, Zhu Dajiang Название: Deep Generative Models, and Data Augmentation, Labelling, and Imperfections: First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in C ISBN: 3030882098 ISBN-13(EAN): 9783030882099 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the First MICCAI Workshop on Deep Generative Models, DG4MICCAI 2021, and the First MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2021, held in conjunction with MICCAI 2021, in October 2021.
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