Learning Bayesian Statistics
#29 Model Assessment, Non-Parametric Models, And Much More, with Aki Vehtari
Dec 2, 2020
Associate professor Aki Vehtari discusses model assessment, non-parametric models like Gaussian processes, and Bayesian probability theory. He talks about teaching Bayesian statistics, open-source software development, and his work on a software-assisted Bayesian workflow. Vehtari shares insights on overcoming challenges in data analysis, model selection, and the dynamic nature of research in the field.
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Quick takeaways
- Aki Vehtari's work spans computational probabilistic modeling, Bayesian probability, and open-source software contributions.
- The importance of model comparison for optimal model selection and avoiding common misconceptions.
Deep dives
Ep1: Akki Vettari's Work
Akki Vettari, an associate professor at Alto University, Finland, discusses his diverse projects encompassing computational probabilistic modeling, Bayesian probability, and open-source software contributions. Vettari's work includes core development of the STAN probabilistic programming framework and involvement in various free software projects. His research interests span Bayesian model assessment, non-parametric models, feature selection, and hierarchical models.
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