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.
Localized Hilbert lift of the feature energy
Definition
Assume AC. Fix an arbitrary probability label space and . Let with its usual real Hilbert inner product, and let Define the indicator to be on and outside it. For , the compositions and are measurable and bounded, and is strongly measurable; hence the scalar integral is finite and the Bochner integral exists. Define The formula evaluates neither integral when . The space is Hilbert for every probability label space and is separable when is countably generated. The latter condition holds for finite labels and for Euclidean Borel labels of any dimension, including joint and triple transport-plan labels. For the flow from a law concentrated on , the particular choice is and . Values of representatives on -null sets do not affect or .
Depends on
Used by
- The Hilbert lift induces the localized Wasserstein continuity equation Lemma
- The localized feature energy is semiconvex along generalized geodesics Lemma
- The localized lifted feature energy is semiconvex Lemma
- The localized lifted subdifferential is a pointwise constrained subdifferential Lemma
- The selected pointwise field is a strong Wasserstein subgradient Lemma
- Finite-particle flows converge to the measure-valued flow in W2 Theorem
Dependency tree · two levels
25 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
- Lénaïc Chizat and Francis Bach, On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport (standard reference, not scraped)
- Luigi Ambrosio, Nicola Gigli, and Giuseppe Savaré, Gradient Flows in Metric Spaces and in the Space of Probability Measures (standard reference, not scraped)