AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking 事件

AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking arXiv:2606.03347v1 Announce Type: cross Abstract: Score-based diffusion models have emerged as prominent deep generative models; however, their application to tabular data remains challenging because their backbones assume fully specified inputs, whereas real-world tabular data often contain missing values. We propose AugMask, a plug-and-play training framework that adapts missing-unaware backb