Independent neural predictors form a low-rank feature map that is aggregated by exact Bayesian linear regression, yielding a finite-rank Student-t process with competitive UCI regression performance.
The log-likelihood ofσ 2 ε is ℓ(σ2 ε) =− N 2 logσ 2 ε − 1 2σ2ε ∥y−Φβ∥ 2 +C, whereCdenotes a constant independent ofσ 2 ε
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Efficient Bayesian Deep Ensembles via Analytic Predictive Inference
Independent neural predictors form a low-rank feature map that is aggregated by exact Bayesian linear regression, yielding a finite-rank Student-t process with competitive UCI regression performance.