Normalizing flows are an established approach for modelling complex
prob...
We review Skilling's nested sampling (NS) algorithm for Bayesian inferen...
The true posterior distribution of a Bayesian neural network is massivel...
We propose a novel method for computing p-values based on nested samplin...
Nested sampling is an important tool for conducting Bayesian analysis in...
It was recently emphasised by Riley (2019); Schittenhelm Wacker (202...
Nested sampling (NS) is an invaluable tool in data analysis in modern
as...
We conduct a thorough analysis of the relationship between the out-of-sa...
We present a principled Bayesian framework for signal reconstruction, in...
We propose a method for transforming probability distributions so that
p...
Nested sampling is an increasingly popular technique for Bayesian
comput...
Nested sampling is an increasingly popular technique for Bayesian comput...