#80 Bayesian Additive Regression Trees (BARTs), with Sameer Deshpande

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch! https://www.pymc-labs.io/ I’m sure you know at least one Bart. Maybe you’ve even used one — but you’re not proud of it, because you didn’t know what you were doing. Thankfully, in this episode, we’ll go to the roots of regression trees — oh yeah, that’s what BART stands for. What were you thinking about? Our tree expert will be no one else than Sameer Deshpande. Sameer is an assistant professor of Statistics at the University of Wisconsin-Madison. Prior to that, he completed a postdoc at MIT and earned his Ph.D. in Statistics from UPenn. On the methodological front, he is interested in Bayesian hierarchical modeling, regression trees, model selection, and causal inference. Much of his applied work is motivated by an interest in understanding the long-term health consequences of playing American-style tackle football. He also enjoys modeling sports data and was a finalist in the 2019 NFL Big Data Bowl. Outside of Statistics, he enjoys cooking, making cocktails, and photography — sometimes doing all of those at the same time… 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, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, 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, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, and Arkady. Visit   / learnbayesstats   to unlock exclusive Bayesian swag ;) Links from the show: Sameer’s website: https://skdeshpande91.github.io/ Sameer on GitHub: https://github.com/skdeshpande91 Sameer on Twitter:   / skdeshpande91   Sameer on Google Scholar: https://scholar.google.com/citations?... LBS #50 Ta(l)king Risks & Embracing Uncertainty, with David Spiegelhalter: https://learnbayesstats.com/episode/5... LBS #51 Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey Clayton: https://learnbayesstats.com/episode/5... LBS #58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng Lao: https://learnbayesstats.com/episode/5... Book Bayesian Modeling and Computation in Python: https://bayesiancomputationbook.com/w... LBS #39 Survival Models & Biostatistics for Cancer Research, with Jacki Buros: https://learnbayesstats.com/episode/3... Original BART paper (Chipman, George, and McCulloch 2010): https://doi.org/10.1214/09-AOAS285 Hill (2011) on BART in causal inference: https://doi.org/10.1198/jcgs.2010.08162 Hahn, Murray, and Carvalho on Bayesian causal forests: https://doi.org/10.1214/19-BA1195 Main BART package in R: https://cran.r-project.org/web/packag... dbart R package: https://cran.r-project.org/web/packag... Sameer’s own re-implementation of BART: https://github.com/skdeshpande91/flex...