2.7k citations · 3.6k across the 79 of their papers we have counts for
86 papers
Diffusion Models for High-Dimensional Clustered Data: Intrinsic-Dimension Adaptivity via Bayesian Classification
Yuga Iguchi, Paul Fearnhead
The empirical success of diffusion models in generative modelling has motivated theoretical work, including quantitative error bounds and qualitative analyses that characterise the…
focus and focus-cpt: Fast Online Changepoint Detection in R and Python
Gaetano Romano, Kes Ward, Yuntang Fan +4
We present an R and Python package for fast online changepoint detection in univariate and multivariate data streams for a variety of models. The package implements the focus famil…
An Efficient Likelihood Ratio Test for Online Changepoint Detection in the Presence of Autocorrelation
Yuntang Fan, Paul Fearnhead, Idris A. Eckley +1
Changepoint detection methods have seen considerable development in recent years, with online algorithms capable of identifying structural changes in streaming data in near real ti…
Tempered Guided Diffusion
Andreas Makris, Paul Fearnhead, Chris Nemeth
Training-free conditional diffusion provides a flexible alternative to task-specific conditional model training, but existing samplers often allocate computation inefficiently: ind…
Scalable Model-Based Clustering with Sequential Monte Carlo
Connie Trojan, Pavel Myshkov, Paul Fearnhead +3
In online clustering problems, there is often a large amount of uncertainty over possible cluster assignments that cannot be resolved until more data are observed. This difficulty…
Detecting interpolation errors in infant mortality counts in 20th Century England and Wales
Tessa Wilkie, Idris Eckley, Paul Fearnhead +1
Understanding historical datasets, such as the England and Wales infant mortality data, for local government districts can provide valuable insights into our changing society. Such…