The article introduces CFM for CNFs, addressing training challenges and improving results in various generative tasks. It discusses OT-CFM for dynamic OT approximation and SB-CFM for Schrödinger bridge inference. Experiments show improved training efficiency and performance in single-cell dynamics, image generation, and unsupervised translation.
In un'altra lingua
dal contenuto originale
arxiv.org
Approfondimenti chiave tratti da
by Alexander To... alle arxiv.org 03-12-2024
https://arxiv.org/pdf/2302.00482.pdfDomande più approfondite