3 papers
stat.ML2026
Universal priors: solving empirical Bayes via Bayesian inference and pretraining
Nick Cannella, Anzo Teh, Yanjun Han +1
We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achieves strong performance on empirical B…
math.ST2026
Function estimation in the empirical Bayes setting
Benjamin Kang, Yury Polyanskiy, Anzo Teh
We study function estimation in the empirical Bayes setting for Poisson and normal means. Specifically, given observations with latent parameters $θ_i\sim π…
cs.LG2025
Solving Empirical Bayes via Transformers
Anzo Teh, Mark Jabbour, Yury Polyanskiy
This work applies modern AI tools (transformers) to solving one of the oldest statistical problems: Poisson means under empirical Bayes (Poisson-EB) setting. In Poisson-EB a high-d…