DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised h-transform

Most recent approaches are motivated heuristically and lack a unifying framework, obscuring connections between them. Further, they often suffer from issues such as being very sensitive to hyperparameters, being expensive to train or needing access to weights hidden behind a closed API.