We establish the first mathematically rigorous link between Bayesian,
va...
Likelihood-based inferences have been remarkably successful in wide-span...
This paper proposes an online, provably robust, and scalable Bayesian
ap...
Discrete state spaces represent a major computational challenge to
stati...
Simulator-based models are models for which the likelihood is intractabl...
Automatic classification of diabetic retinopathy from retinal images has...
Generalised Bayesian inference updates prior beliefs using a loss functi...
Complex simulators have become a ubiquitous tool in many scientific
disc...
Gaussian Processes (GPs) can be used as flexible, non-parametric functio...
Models of discrete-valued outcomes are easily misspecified if the data
e...
This paper investigates Frequentist consistency properties of the poster...
This report provides an in-depth overview over the implications and nove...
This paper introduces a generalized representation of Bayesian inference...
We present the very first robust Bayesian Online Changepoint Detection
a...
Bayesian On-line Changepoint Detection is extended to on-line model sele...