Tag: dkgm

Debiasing Kernel-Based Generative Models arXiv:2503.20825v1 Announce Type: new Abstract: We propose a novel two-stage framework of generative models named Debiasing Kernel-Based Generative Models (DKGM) with the insights from kernel density estimation (KDE) and stochastic approximation. In the first stage of DKGM, we employ KDE to bypass the obstacles in estimating the density of data without…