AI RESEARCH
The Score-Difference Flow for Implicit Generative Modeling
arXiv CS.LG
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ArXi:2304.12906v4 Announce Type: replace Implicit generative modeling (IGM) aims to produce samples of synthetic data matching the characteristics of a target data distribution. Recent work (e.g. score-matching networks, diffusion models) has approached the IGM problem from the perspective of pushing synthetic source data toward the target distribution via dynamical perturbations or flows in the ambient space.