2 papers
stat.ML2019
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…
stat.ML2018
Nonparametric learning from Bayesian models with randomized objective functions
S. P. Lyddon, S. G. Walker, C. C. Holmes
Bayesian learning is built on an assumption that the model space contains a true reflection of the data generating mechanism. This assumption is problematic, particularly in comple…