An appraisal of approximation error in variational inference

Silvelyn Zwanzig and Rauf Ahmad

Statistics & Probability Letters, 2025, vol. 226, issue C

Abstract: We show that in a linear model setting, the minimization problem in variational inference pertains to approximation error under suitable prior. We further show that the choice of prior preferred by the approximating member in mean-field family trades itself off with model assumptions. To demonstrate this, we also prove a result of general interest for linear algebra.

Keywords: Bayesian theory; Mean-field family; Kullback–Leibler criterion (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.spl.2025.110505

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