4 papers
Approximate Bayesian Fusion
Filippo Pagani, Adam M. Johansen, Gareth O. Roberts
Distributed inference plays an important role in modern computational statistics and machine learning. In the frequentist setting, methods can often aggregate results by simply ave…
A discomfort-informed adaptive Gibbs sampler for finite mixture models
Davide Fabbrico, Andi Q. Wang, Sebastiano Grazzi +5
Finite mixture models are frequently used to uncover latent structures in high-dimensional datasets (e.g.\ identifying clusters of patients in electronic health records). The infer…
Annealed variational mixtures for disease subtyping and biomarker discovery
Emma Prevot, Rory Toogood, Filippo Pagani +1
Cluster analyses of high-dimensional data are often hampered by the presence of large numbers of variables that do not provide relevant information, as well as the perennial issue…
FlexKnot and Gaussian Process for 21 cm global signal analysis and foreground separation
Stefan Heimersheim, Leiv Rønneberg, Henry Linton +2
The cosmological 21 cm signal is one of the most promising avenues to study the Epoch of Reionization. One class of experiments aiming to detect this signal is global signal experi…