Why these three criteria: negative log evidence equals the area under the loss curve
BlackHC · x · 2026-09-09
The theoretical justification: for an ideal Bayesian learner, using the chain rule of probability, negative log evidence is exactly the area under its loss curve. Hence the three criteria — validation loss estimates the endpoint, CLML is a tail area, and (Bayesian) evidence scores the whole trajectory.
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