3 papers
stat.ML2026
Transformers Can Learn Posterior Predictive Distributions In-Context
Gyeonghun Kang, Changwoo J. Lee, Xiang Cheng
Prior-data fitted networks (PFNs) have recently emerged as a powerful approach for Bayesian prediction tasks, approximating the posterior predictive distribution (PPD) through in-c…
stat.ME2026
Multiscale Cochran-Mantel-Haenszel Scanning for Conditional Dependency
Gyeonghun Kang, Jialiang Mao, Li Ma
We propose a nonparametric approach to testing conditional independence and estimating conditional association, generalizing the Cochran-Mantel-Haenszel (CMH) test and odds-ratio e…
stat.ME2023
Model selection-based estimation for generalized additive models using mixtures of g-priors: Towards systematization
Gyeonghun Kang, Seonghyun Jeong
We explore the estimation of generalized additive models using basis expansion in conjunction with Bayesian model selection. Although Bayesian model selection is useful for regress…