Statistical mechanics formulas predict universal-to-specialisation phase transitions and Bayes-optimal generalization errors for extensive-width two-layer Bayesian networks at interpolation.
(61) We have used the fact that⟨ · ⟩ˆB(v) is symmetric if the prior PW is, thus forcing us to match j with p if i ̸= l
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Statistical mechanics of extensive-width Bayesian neural networks near interpolation
Statistical mechanics formulas predict universal-to-specialisation phase transitions and Bayes-optimal generalization errors for extensive-width two-layer Bayesian networks at interpolation.