Learning Bayesian Statistics

Do you know what proteins are, what they do and why they are useful? Well, be prepared to be amazed! In this episode, Seth Axen will tell us about the fascinating world of protein structures and computational biology, and how his work of Bayesian modeler fits into that!

Passionate about mathematics and statistics, Seth is finishing a PhD in bioinformatics at the Sali Lab of the University of California, San Francisco (UCSF). His research interests span the broad field of computational biology: using computer science, mathematics, and statistics to understand biological systems. His current research focuses on inferring protein structural ensembles. 

Open source development is also very dear to his heart, and indeed he contributes to many open source packages, especially in the Julia ecosystem. In particular, he develops and maintains ArviZ.jl, the Julia port of ArviZ, a platform-agnostic python package to visualize and diagnose your Bayesian models. Seth will tell us how he became involved in ArviZ.jl, what its strengths and weaknesses are, and how it fits into the Julia probabilistic programming landscape.

Ow, and as a bonus, you’ll discover why Seth is such a fan of automatic differentiation, aka « autodiff » — I actually wanted to edit this part out but Seth strongly insisted I kept it. Just kidding of course — or, am I… ?

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

Links from the show:

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 and Paul Oreto.

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