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Causal Bandits Podcast
Causal Bandits Podcast with Alex Molak is here to help you learn about causality, causal AI and causal machine learning through the genius of others.
The podcast focuses on causality from a number of different perspectives, finding common grounds between academia and industry, philosophy, theory and practice, and between different schools of thought, and traditions.
Your host, Alex Molak is an a machine learning engineer, best-selling author, and an educator who decided to travel the world to record conversations with the most interesting minds in causality to share them with you.
Enjoy and stay causal!
Keywords: Causal AI, Causal Machine Learning, Causality, Causal Inference, Causal Discovery, Machine Learning, AI, Artificial Intelligence
Causal Bandits Podcast
Causal Inference & the "Bayesian-Frequentist War" | Richard Hahn S2E8 | CausalBanditsPodcast.com
*What can we learn about causal inference from the “war” between Bayesians and frequentists?*
What can we learn about causal inference from the “war” between Bayesians and frequentists?
In the episode, we cover:
- What can we learn from the “war” between Bayesians and frequentists?
- Why do Bayesian Additive Regression Trees (BART) “just work”?
- Do heterogeneous treatment effects exist?
- Is RCT generalization a heterogeneity problem?
In the episode, we accidentally coined a new term: “feature-level selection bias.”
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Video version available on the Youtube:
https://youtu.be/-hRS8eU3Tow
Recorded in Arizona, US.
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*About The Guest*
Professor Richard Hahn, PhD, is a professor of statistics at Arizona State University (ASU). He develops novel statistical methods for analyzing data arising from the social sciences, including psychology, economics, education, and business. His current focus revolves around causal inference using regression tree models, as well as foundational issues in Bayesian statistics.
Connect with Richard:
- Richard on LinkedIn: https://www.linkedin.com/in/richard-hahn-a1096050/
- Richard's web page: https://methodologymatters.substack.com/about
*About The Host*
Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).
Connect with Alex:
- Alex on the Internet: https://bit.ly/aleksander-molak
*Links*
Repo
- https://stochtree.ai
Papers
- Hahn et al (2020) - "Bayesian Regression Tree Models for Causal Inference" (https://projecteuclid.org/journals/bayesian-analysis/volume-15/issue-3/Bayesian-Regression-Tree-Models-for-Causal-Inference--Regularization-Confounding/10.1214/19-BA1195.full)
- Yeager, ..., Dweck et al (2019) - "A national experiment reveals where a growth mindset improves achievement" (https://www.nature.com/articles/s41586-019-1466-y)
- Herren, Hahn, et al (20
Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4