How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Small-ball MAP conventions and Cameron–Martin relative modes
Definition
Let be a separable Banach space with norm , and let be a Borel probability measure on . For and , write and . A strong small-ball MAP is a point for which Assume AC for the covariance-induced Cameron–Martin notation. In this Gaussian branch, regard as a real Banach space, restricting scalars if is complex; denotes its continuous real dual, and Gaussianity is tested against these real functionals. The norm, Borel sets, and balls are unchanged by this restriction. If is a posterior law formed by weighting a centered Borel Gaussian prior on , let be its covariance operator and let be the completion of with inner product ; the canonical injection extends . A Cameron–Martin ratio mode is a point such that, for every , the denominator is positive for all sufficiently small and exists and is at least . This pairwise comparison over fixed Cameron–Martin centers does not assert the global strong small-ball MAP condition.
For every , : a countable dense subset gives a countable cover of by radius- open balls, each contained in its corresponding closed ball, and countable subadditivity rules out all such closed balls having zero probability.
Definition references
the posterior is the normalized likelihood-potential weighting of a prior
a Borel prior is concentrated on its declared forward-map domain
the covariance-dual quotient, Cameron–Martin norm, and canonical injection
a separable space has an at most countable dense subset
countable subadditivity prevents a probability space from being a countable union of null balls
the Axiom of Choice assumed for the Gaussian covariance/RKHS branch
a Borel probability is a probability measure on the Borel sigma-algebra
a Banach space is complete in its norm metric
restriction to real scalars preserves the norm and metric of a complex Banach space
Depends on
- The Axiom of Choice
- Misfit evidence and the potential posterior law
- A Borel prior concentrated on a forward-map domain
- Banach space
- Realification preserves a complex norm and its metric
- Covariance operator and reproducing-kernel Hilbert space of a Banach Gaussian
- Borel probability law on a polish space
- Separability: the existence of an at most countable dense subset
- Finite and countable subadditivity of measures
Used by
- An infinite-dimensional Gaussian has no locally finite translation-invariant density reference Counterexample
- Finite-dimensional small-ball MAP equals the density mode Example
- The posterior mean need not be a small-ball MAP Example
- Gaussian posterior small-ball ratios and the Onsager–Machlup functional Theorem
Dependency tree · two levels
51 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- M. Dashti, K. J. H. Law, A. M. Stuart, and J. Voss, MAP Estimators and Their Consistency in Bayesian Nonparametric Inverse Problems (standard reference, not scraped)
- H. Kekkonen and Y. Korolev, Inverse Problems, lecture notes (standard reference, not scraped)