Sobolev Regularized Score Difference Estimation in Diffusion Models

We propose a Sobolev-regularized classification framework for score difference estimation in diffusion models, resolving gradient divergence issues in standard transfer learning. The method improves ECG generation from PTB-XL to ICBEB2018 and achieves stronger robustness in small-sample regimes.