2 papers
stat.ML2026
Optimal Stopping in Latent Diffusion Models
Yu-Han Wu, Quentin Berthet, Gérard Biau +3
We identify and analyze a surprising phenomenon of Latent Diffusion Models (LDMs) where the final steps of the diffusion can degrade sample quality. In contrast to conventional arg…
stat.ML2026
When Pattern-by-Pattern Works: Theoretical and Empirical Insights for Logistic Models with Missing Values
Christophe Muller, Erwan Scornet, Julie Josse
Predicting with missing inputs challenges even parametric models, as parameter estimation alone is insufficient for prediction on incomplete data. While several works study predict…