Answers.Body: <p>From the theoretical foundations one can look into the <code>Chapter 20: Deep Generative Models</code> of the classic DL book by <strong>Goodfellow, Bengio</strong> <a href="https://amzn.to/2MmZNbH" rel="nofollow noreferrer">https://amzn.to/2MmZNbH</a>. Not the most recent reference, but written by the professionals in simple and accessible way.</p>
  <p>There is a nice book <strong>Generative Deep Learning</strong> by D.Foster with some simple heuristics and probability theory motivations and examples <a href="https://www.google.ru/books/edition/Generative_Deep_Learning/RqegDwAAQBAJ?hl=en&amp;gbpv=1&amp;printsec=frontcover" rel="nofollow noreferrer">https://www.google.ru/books/edition/Generative_Deep_Learning/RqegDwAAQBAJ?hl=en&amp;gbpv=1&amp;printsec=frontcover</a>.</p>
  <p>Finally, there is a book from Jason Brownlee (author of many nicely written articles on machinelearningmastery.com) <a href="https://machinelearningmastery.com/generative_adversarial_networks/" rel="nofollow noreferrer">https://machinelearningmastery.com/generative_adversarial_networks/</a></p>
  
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Answers.CreationDate: 2021-07-04T13:21:48.583Z
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Body: <p>Generative models in artificial intelligence span from simple models like Naive Bayes to the advanced deep generative models like current day GANs. This question is not about coding and involves only science and theoretical part only.</p>
  <p>Are there any standard textbooks that covers topics from scratch to the advanced?</p>
  
Tags: <generative-model><resource-request>
Title: Book(s) on generative models
UserDisplayName: hanugm
ThreadText: # Book(s) on generative models
  
  (Asked by: username_0 on 2021-07-04)
  
  Generative models in artificial intelligence span from simple models like Naive Bayes to the advanced deep generative models like current day GANs. This question is not about coding and involves only science and theoretical part only.
  
  Are there any standard textbooks that covers topics from scratch to the advanced?
  
  **Tags:** generative-model, resource-request
  
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  ## 1 answers
  
  ### Answer by username_1 on 2021-07-04. Score: 4
  
  From the theoretical foundations one can look into the `Chapter 20: Deep Generative Models` of the classic DL book by **Goodfellow, Bengio** <https://amzn.to/2MmZNbH>. Not the most recent reference, but written by the professionals in simple and accessible way.
  
  There is a nice book **Generative Deep Learning** by D.Foster with some simple heuristics and probability theory motivations and examples <https://www.google.ru/books/edition/Generative_Deep_Learning/RqegDwAAQBAJ?hl=en&gbpv=1&printsec=frontcover>.
  
  Finally, there is a book from Jason Brownlee (author of many nicely written articles on machinelearningmastery.com) <https://machinelearningmastery.com/generative_adversarial_networks/>
  
  
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