https://probml.github.io/pml-book/book2.html

Probabilistic Machine Learning: Advanced Topics

by Kevin Patrick Murphy.
MIT Press, 2023.

Book cover

Key links

  * Short table of contents
  * Long table of contents
  * Preface
  * Draft pdf of the main book, 2022-02-28. CC-BY-NC-ND license.
    (Please cite the official reference below.)
  * Draft pdf of the supplementary material, 2022-02-27. CC-BY-NC-ND
    license. (Please cite the official reference below.)
  * Issue tracker.
  * Code to recreate all the figures is stored in the pyprobml repo.
    You can access it by clicking on links in the pdf file.
  * Mailing list for major announcements (Low traffic)
  * Acknowledgements

If you use this book, please be sure to cite

 @book{pml2Book,
 author = "Kevin P. Murphy",
 title = "Probabilistic Machine Learning: Advanced Topics",
 publisher = "MIT Press",
 year = 2023,
 url = "probml.ai"
}

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Table of contents

TOC 2022-02-27

Acknowledgements

I would like to thank the following people for helping with this
book.

  * People who helped write some of the sections (details in the
    preface): Alex Alemi (Google), Marco Cuturi (Apple, work done at
    Google), Jeff Bilmes (U. Washington), Justin Gilmer (Google), Roy
    Frostig (Google), Andrew Wilson (NYU), George Papamakarios
    (Deepmind), Balaji Lakshminarayanan (Google), Yang Song
    (Stanford), Durk Kingma (Google), Mihaela Rosca (Deepmind / UCL),
    Shakir Mohamed (Deepmind), Vinayak Rao (Purdue), Ben Poole
    (Google), Simon Kornblith (Google), Been Kim (Google), Finale
    Doshi-Velez (Harvard), Lihong Li (Amazon, work done at Google),
    Victor Veitch (Google / U. Chicago), Alexander D'Amour (Google).
  * People who helped with the code and figures: Mahmoud Soliman,
    Aleyna Kara, Gerardo Duran-Martin and others listed here.