BITESIZE Making Variational Inference Reliable: From ADVI to DADVI

Today’s clip is from episode 147 of the podcast, with Martin Ingram. Alex and Martin discuss the intricacies of variational inference, particularly focusing on the ADVI method and its challenges. They explore the evolution of approximate inference methods, the significance of mean field variational inference, and the innovative linear response technique for covariance estimation. The discussion also delves into the trade-offs between stochastic and deterministic optimization techniques, providing insights into their implications for Bayesian statistics. Get the full discussion here . 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 ;) Transcript This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.

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BITESIZE Making Variational Inference Reliable: From ADVI to DADVI is an episode from Learning Bayesian Statistics by Alexandre ANDORRA.

This episode is 00:21:59 long.

This episode was published on Dec 17, 2025.

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