3 papers
stat.ME2026
Penalizing complexity priors for Bayesian inference of circular models
Xiang Ye, Janet Van Niekerk, HÃ¥vard Rue
Advancements in computational power and methodologies have enabled research on massive datasets. However, tools for analyzing data with directional or periodic characteristics, suc…
cs.LG2026
SIGMA: Scalable Spectral Insights for LLM Model Collapse
Yi Gu, Lingyou Pang, Xiangkun Ye +4
The rapid adoption of synthetic data for training Large Language Models (LLMs) has introduced the technical challenge of "model collapse"-a degenerative process where recursive tra…
stat.ME2026
A Bayesian regression framework for circular models with INLA
Xiang Ye, Janet Van Niekerk, Haavard Rue
Regression models for circular variables are less developed, since the concept of building a linear predictor from linear combinations of covariates and various random effects, bre…