Episode 29

#29 Model Assessment, Non-Parametric Models, And Much More, with Aki Vehtari

I’ll be honest here: I had a hard time summarizing this episode for you, and, let’s face it, it’s all my guest’s fault! Why? Because Aki Vehtari works on so many interesting projects that it’s hard to sum them all up, even more so because he was very generous with his time for this episode! But let’s try anyway, shall we?

So, Aki is an Associate professor in computational probabilistic modeling at Aalto University, Finland. You already heard his delightful Finnish accent on episode 20, with Andrew Gelman and Jennifer Hill, talking about their latest book, « Regression and other stories ». He is also a co-author of the popular and awarded book « Bayesian Data Analysis », Third Edition, and a core-developer of the seminal probabilistic programming framework Stan.

An enthusiast of open-source software, Aki is a core-contributor to the ArviZ package and has been involved in many free software projects such as GPstuff for Gaussian processes and ELFI for likelihood inference.

His numerous research interests are Bayesian probability theory and methodology, especially model assessment and selection, non-parametric models (such as Gaussian processes), feature selection, dynamic models, and hierarchical models.

We talked about all that — and more — on this episode, in the context of his teaching at Aalto and the software-assisted Bayesian workflow he’s currently working on with a group of researchers.

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

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Vincent Arel-Bundock, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho and Colin Carroll.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

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About the Podcast

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Learning Bayesian Statistics
A podcast on Bayesian inference - the methods, the projects and the people who make it possible!

About your host

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Alexandre ANDORRA

Hi! I'm your host, Alex Andorra. By day, I'm a Bayesian modeler at the PyMC Labs consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the awesome Python packages PyMC and ArviZ.

An always-learning statistician, I love building models and studying elections and human behavior. I also love Nutella a bit too much, but I don't like talking about it – I prefer eating it.

My goal is to make this podcast as interesting and useful to you as possible. So, hit me on Twitter or email with your questions and suggestions!