#142 Bayesian Trees & Deep Learning for Optimization & Big Data, with Gabriel Stechschulte

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

• Get early access to Alex's next live-cohort courses!
• Intro to Bayes Course (first 2 lessons free)
• Advanced Regression Course (first 2 lessons free)

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:

• BART as a core tool: Gabriel explains how Bayesian Additive Regression Trees provide robust uncertainty quantification and serve as a reliable baseline model in many domains.
• Rust for performance: His Rust re-implementation of BART dramatically improves speed and scalability, making it feasible for larger datasets and real-world IoT applications.
• Strengths and trade-offs: BART avoids overfitting and handles missing data gracefully, though it is slower than other tree-based approaches.
• Big data meets Bayes: Gabriel shares strategies for applying Bayesian methods with big data, including when variational inference helps balance scale with rigor.
• Optimization and decision-making: He highlights how BART models can be embedded into optimization frameworks, opening doors for sequential decision-making.
• Open source matters: Gabriel emphasizes the importance of communities like PyMC and Bambi, encouraging newcomers to start with small contributions.

Chapters:

05:10 – From economics to IoT and Bayesian statistics

18:55 – Introduction to BART (Bayesian Additive Regression Trees)

24:40 – Re-implementing BART in Rust for speed and scalability

32:05 – Comparing BART with Gaussian Processes and other tree methods

39:50 – Strengths and limitations of BART

47:15 – Handling missing data and different likelihoods

54:30 – Variational inference and big data challenges

01:01:10 – Embedding BART into optimization and decision-making frameworks

01:08:45 – Open source, PyMC, and community support

01:15:20 – Advice for newcomers

01:20:55 – Future of BART, Rust, and probabilistic programming

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, 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 Cost