Diff-CA: Separating Common and Salient Factors with Diffusion Models 事件

Diff-CA: Separating Common and Salient Factors with Diffusion Models arXiv:2606.06120v1 Announce Type: new Abstract: Contrastive Analysis aims to separate factors that are common between two data distributions from those that are salient to only one of them. Existing contrastive methods are based on generative models (e.g., VAEs or GANs) that often suffer from limited reconstruction and image quality, which hampers effective latent factor separation and limits their applicability to high-fideli