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1. |
Record Nr. |
UNINA9910886987803321 |
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Autore |
Tomczak Jakub M |
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Titolo |
Deep Generative Modeling / / by Jakub M. Tomczak |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[2nd ed. 2024.] |
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Descrizione fisica |
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1 online resource (325 pages) |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Machine learning |
Computer science - Mathematics |
Mathematical statistics |
Computer simulation |
Artificial Intelligence |
Machine Learning |
Probability and Statistics in Computer Science |
Computer Modelling |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1 Why Deep Generative Modeling? -- Chapter 2 Probabilistic modeling: From Mixture Models to Probabilistic Circuits -- Chapter 3 Autoregressive Models -- Chapter 4 Flow-based Models -- Chapter 5 Latent Variable Models -- Chapter 6 Hybrid Modeling -- Chapter 7 Energy-based Models -- Chapter 8 Generative Adversarial Networks -- Chapter 9 Score-based Generative Models -- Chapter 10 Deep Generative Modeling for Neural Compression -- Chapter 11 From Large Language Models to Generative AI. |
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Sommario/riassunto |
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This first comprehensive book on models behind Generative AI has been thoroughly revised to cover all major classes of deep generative models: mixture models, Probabilistic Circuits, Autoregressive Models, Flow-based Models, Latent Variable Models, GANs, Hybrid Models, Score-based Generative Models, Energy-based Models, and Large |
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Language Models. In addition, Generative AI Systems are discussed, demonstrating how deep generative models can be used for neural compression. All chapters are accompanied by code snippets that help to better understand the modeling frameworks presented. 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 of machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It should appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics who wish to get familiar with deep generative modeling. In order to engage with a reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on the author's GitHub site: github.com/jmtomczak/intro_dgm 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. |
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2. |
Record Nr. |
UNINA9910959340803321 |
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Autore |
Hattaway Herman |
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Titolo |
Shades of blue and gray : an introductory military history of the Civil War / / Herman Hattaway |
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Pubbl/distr/stampa |
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Columbia ; ; London, : University of Missouri Press, c1997 |
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ISBN |
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Descrizione fisica |
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Disciplina |
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Soggetti |
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Military weapons - United States - History - 19th century |
Military art and science - United States - History - 19th century |
Strategy - History - 19th century |
United States History Civil War, 1861-1865 Campaigns |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Sommario/riassunto |
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An introductory military history of the American Civil War, Shades of Blue and Gray places the 1861-1865 conflict within the broad context of evolving warfare. Emphasizing technology and its significant impact, Hattaway includes valuable material on land and sea mines, minesweepers, hand grenades, automatic weapons, the Confederate submarine, and balloons. The evolution of professionalism in the American military serves as an important connective theme throughout. Hattaway extrapolates from recent works by revisionists William Skelton and Roy Roberts to illustrate convincingly that the development of military professionalism is not entirely a post-Civil War phenomenon. The author also incorporates into his work important new findings of recent scholars such as Albert Castel (on the Atlanta Campaign), Reid Mitchell (on soldiers' motivation), Mark Grimsley (on "hard war"), Brooks D. Simpson (on Ulysses S. Grant), and Lauren Cook Burgess (on women who served as soldiers, disguised as men). In addition, Hattaway comments on some of the best fiction and nonfiction available in his recommended reading lists, which will both enlighten and motivate readers. Informative and clearly written, enhanced by graceful prose |
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and colorful anecdotes, Shades of Blue and Gray will appeal to all general readers. |
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