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stat.ME2026
Bagged Martingale Posteriors: Calibrated Uncertainty Quantification for Predictive Resampling
Hui Wang, Edwin Fong, David T. Frazier
Martingale posteriors and related predictive resampling methods replace the likelihood--prior pair used within Bayesian inference with a predictive model for future observations. T…
stat.ME2026
On the design distribution for predictive Bayesian regression
Wanyue Sun, Edwin Fong
The predictive approach to Bayesian inference accesses the posterior distribution via a sequence of one-step-ahead predictives, enabling inference via predictive resampling without…
stat.ME2025
TabMGP: Martingale Posterior with TabPFN
Kenyon Ng, Edwin Fong, David T. Frazier +2
Bayesian inference provides principled uncertainty quantification but is often limited by the challenges of prior and likelihood elicitation. The martingale posterior (MGP) (Fong e…