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#133 Making Models More Efficient & Flexible, with Sean Pinkney & Adrian Seyboldt

Learning Bayesian Statistics

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Navigating Statistical Modeling Challenges

This chapter explores the complexities of statistical modeling, specifically focusing on the intricacies of creating positive correlation matrices and the challenges involved in sampling techniques. The dialogue includes collaborative problem-solving around advanced methodologies, Cholesky parameterizations, and innovative sampling methods using TensorFlow Probability. Additionally, the discussion touches on philosophical reflections on broader global issues, highlighting the importance of combining technical expertise with awareness of societal challenges.

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