Notes on generative modeling: flow matching, diffusion, optimal transport and Schr{ö}dinger bridge
arXiv:2606.300533.1
Predicted impact top 80% in ML · last 90 daysOriginality Synthesis-oriented
AI Analysis
For researchers in generative modeling, this offers a conceptual synthesis but is purely expository and incremental.
This paper provides a unified mathematical perspective on generative modeling techniques, showing connections between optimal transport, Schrödinger bridge, and flow matching. It does not present new results or empirical evaluations.
These notes recapitulate the high level mathematical principles behind different techniques for generative modeling. I show the connections between optimal transport and standard techniques such as Schr{ö}dinger bridge and flow matching.