What is recorded here?
Specified paths between endpoint samples and learned probability-current velocities through quadratic regression objectives; extended the construction with latent noise to relate deterministic flows, scores and tunable diffusions.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Population identities assume the stated density, smoothness and integrability conditions; they do not give exact finite-network transport. Closely related Flow Matching and rectified-flow work retain separate credited precedence, not new invention here. Arbitrary interpolants are not automatically optimal transport or Schrödinger bridges; further optimization is needed.
Read the original work
- Building Normalizing Flows with Stochastic Interpolants
- Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Michael S. Albergo; Eric Vanden-Eijnden; Nicholas M. Boffi
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Stochastic interpolants: variational velocity and score learning
Specified paths between endpoint samples and learned probability-current velocities through quadratic regression objectives; extended the construction with latent noise to relate deterministic flows, scores and tunable diffusions.
Scientific scope
Population identities assume the stated density, smoothness and integrability conditions; they do not give exact finite-network transport. Closely related Flow Matching and rectified-flow work retain separate credited precedence, not new invention here. Arbitrary interpolants are not automatically optimal transport or Schrödinger bridges; further optimization is needed.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Michael S. Albergo; Eric Vanden-Eijnden; Nicholas M. Boffi
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.