2 papers
stat.ML2026
Quantifying Error Propagation and Model Collapse in Diffusion Models
Nail B. Khelifa, Richard E. Turner, Ramji Venkataramanan
Machine learning models are increasingly trained or fine-tuned on synthetic data. Recursively training on such data has been observed to significantly degrade performance in a wide…
stat.ML2025
Bayesian Circular Regression with von Mises Quasi-Processes
Yarden Cohen, Alexandre Khae Wu Navarro, Jes Frellsen +3
The need for regression models to predict circular values arises in many scientific fields. In this work we explore a family of expressive and interpretable distributions over circ…