3 citations · 3 across the 2 of their papers we have counts for
4 papers
A Predictive Approach to Bayesian Nonparametric Survival Analysis
Edwin Fong, Brieuc Lehmann
Bayesian nonparametric methods are a popular choice for analysing survival data due to their ability to flexibly model the distribution of survival times. These methods typically e…
Conformal Bayesian Computation
Edwin Fong, Chris Holmes
We develop scalable methods for producing conformal Bayesian predictive intervals with finite sample calibration guarantees. Bayesian posterior predictive distributions, $p(y \mid…
On the marginal likelihood and cross-validation
Edwin Fong, Chris Holmes
In Bayesian statistics, the marginal likelihood, also known as the evidence, is used to evaluate model fit as it quantifies the joint probability of the data under the prior. In co…
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
Edwin Fong, Simon Lyddon, Chris Holmes
Increasingly complex datasets pose a number of challenges for Bayesian inference. Conventional posterior sampling based on Markov chain Monte Carlo can be too computationally inten…