Author

Wen-Lin Dai

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Preprint Oct 2026

Synthetic Data Augmentation for Functional Data: Wasserstein Risk Bounds and Diffusion-Based Conditional Generation

Functional data are costly to collect; samples of tens to hundreds of curves are common. Synthetic data augmentation can help, but its theory is developed for finite-dimensional data and relies on total variation, which is uninformative for functions. We study augmentation with a class-conditional functional diffusion...

Yu-Hao Qi, Wen-Lin Dai, Xue-Hu Zhu · 0 citations

Preprint Sep 2026

Reference-Null Calibrated Thresholds for E-Processes with Applications to Conformal Martingales

E-processes provide a flexible framework for anytime-valid inference, with the conventional rejection boundary $1/\alpha$ typically justified by Ville's inequality. Such a boundary is universal but can be conservative, as it does not exploit additional information about the null distribution. We propose a reference-nul...

Yi Ding, Lan Wei, Xue-Hu Zhu et al. · 1 citation