Topics — What a work is about. Nucleation holds whatever reading the owner files here, whether or not an Anthology of the SOTA topic could also hold it; instruction for ML practice belongs to the anthology (ADR-048). The words are seeded from the clusters the reading-time triage of 2026-09-25 found, and grow by decision.
Model comparison — choosing between models by their evidence — the marginal likelihood and Bayes factors, the Savage–Dickey density ratio for nested models, Occam factors and the evidence framework, Bayesian model reduction and structure learning, and information criteria and free energies for singular models (ADR-026).
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