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.
Generalized W2 geodesics and strong Wasserstein subgradients
Definition
Assume AC. Let . A generalized geodesic from to with base is a probability measure on triples whose marginal is an optimal coupling of and and whose marginal is an optimal coupling of and ; its interpolating curve is . A functional is -convex along generalized geodesics if for every such its values satisfy . A vector field is a strong Wasserstein subgradient of at if for every and every coupling of and , as the coupling action tends to zero, with a remainder uniform over all such couplings. The definition imposes no global displacement-convexity claim.
Depends on
Used by
Dependency tree · two levels
26 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
- Luigi Ambrosio, Gigli, and Giuseppe Savaré, Gradient Flows in Metric Spaces and in the Space of Probability Measures (standard reference, not scraped)
- Lénaïc Chizat and Francis Bach, On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport (standard reference, not scraped)