3 papers
math.NA2026
Geometry-Preserving Encoder/Decoder in Latent Generative Models
Wonjun Lee, Riley C. W. O'Neill, Dongmian Zou +2
Generative modeling aims to generate new data samples that resemble a given dataset. When using diffusion models for this task, one of the main challenges is solving the problem in…
cs.LG2026
Understanding Latent Diffusability via Fisher Geometry
Jing Gu, Morteza Mardani, Wonjun Lee +2
Diffusion models often degrade in latent spaces, yet the formal causes remain poorly understood. We quantify latent-space diffusability via the rate of change of the Minimum Mean S…
cs.LG2025
Stein Discrepancy for Unsupervised Domain Adaptation
Anneke von Seeger, Dongmian Zou, Gilad Lerman
Unsupervised domain adaptation (UDA) aims to improve model performance on an unlabeled target domain using a related, labeled source domain. A common approach aligns source and tar…