• #118 Exploring the Future of Stan, with Charles Margossian & Brian Ward

  • 2024/10/30
  • 再生時間: 59 分
  • ポッドキャスト

#118 Exploring the Future of Stan, with Charles Margossian & Brian Ward

  • サマリー

  • Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!

    • My Intuitive Bayes Online Courses
    • 1:1 Mentorship with me

    Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!

    Visit our Patreon page to unlock exclusive Bayesian swag ;)

    Takeaways:

    • User experience is crucial for the adoption of Stan.
    • Recent innovations include adding tuples to the Stan language, new features and improved error messages.
    • Tuples allow for more efficient data handling in Stan.
    • Beginners often struggle with the compiled nature of Stan.
    • Improving error messages is crucial for user experience.
    • BridgeStan allows for integration with other programming languages and makes it very easy for people to use Stan models.
    • Community engagement is vital for the development of Stan.
    • New samplers are being developed to enhance performance.
    • The future of Stan includes more user-friendly features.

    Chapters:

    00:00 Introduction to the Live Episode

    02:55 Meet the Stan Core Developers

    05:47 Brian Ward's Journey into Bayesian Statistics

    09:10 Charles Margossian's Contributions to Stan

    11:49 Recent Projects and Innovations in Stan

    15:07 User-Friendly Features and Enhancements

    18:11 Understanding Tuples and Their Importance

    21:06 Challenges for Beginners in Stan

    24:08 Pedagogical Approaches to Bayesian Statistics

    30:54 Optimizing Monte Carlo Estimators

    32:24 Reimagining Stan's Structure

    34:21 The Promise of Automatic Reparameterization

    35:49 Exploring BridgeStan

    40:29 The Future of Samplers in Stan

    43:45 Evaluating New Algorithms

    47:01 Specific Algorithms for Unique Problems

    50:00 Understanding Model Performance

    54:21 The Impact of Stan on Bayesian Research

    Thank you to my Patrons for making this episode possible!

    Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin...

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あらすじ・解説

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!

  • My Intuitive Bayes Online Courses
  • 1:1 Mentorship with me

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!

Visit our Patreon page to unlock exclusive Bayesian swag ;)

Takeaways:

  • User experience is crucial for the adoption of Stan.
  • Recent innovations include adding tuples to the Stan language, new features and improved error messages.
  • Tuples allow for more efficient data handling in Stan.
  • Beginners often struggle with the compiled nature of Stan.
  • Improving error messages is crucial for user experience.
  • BridgeStan allows for integration with other programming languages and makes it very easy for people to use Stan models.
  • Community engagement is vital for the development of Stan.
  • New samplers are being developed to enhance performance.
  • The future of Stan includes more user-friendly features.

Chapters:

00:00 Introduction to the Live Episode

02:55 Meet the Stan Core Developers

05:47 Brian Ward's Journey into Bayesian Statistics

09:10 Charles Margossian's Contributions to Stan

11:49 Recent Projects and Innovations in Stan

15:07 User-Friendly Features and Enhancements

18:11 Understanding Tuples and Their Importance

21:06 Challenges for Beginners in Stan

24:08 Pedagogical Approaches to Bayesian Statistics

30:54 Optimizing Monte Carlo Estimators

32:24 Reimagining Stan's Structure

34:21 The Promise of Automatic Reparameterization

35:49 Exploring BridgeStan

40:29 The Future of Samplers in Stan

43:45 Evaluating New Algorithms

47:01 Specific Algorithms for Unique Problems

50:00 Understanding Model Performance

54:21 The Impact of Stan on Bayesian Research

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin...

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