Author

Edwin Fong

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Preprint Oct 2026

Recursive moment updates for scalable Bayesian nonparametric regression

Bayesian nonparametric regression methods have wide applications in statistics and machine learning, but inference can often be expensive or require approximations. This paper introduces a class of recursive moment function updates which are closed form, interpretable, expedient, and fully quantify Bayesian uncertainty...

Peter Liu, Andrew Yiu, Edwin Fong · 0 citations

Preprint Oct 2026

Martingale Posterior Cox Processes

Cox processes provide a principled Bayesian nonparametric framework for modeling event-based data through an underlying intensity function. However, existing inference methods for estimating the intensity typically rely on computationally expensive Markov chain Monte Carlo sampling or approximate inference techniques....

J. Rooijakkers, Edwin Fong · 0 citations