Particle filters for mixture models with an unknown number of components. - Paul Fearnhead (Stat. Comput., 2004)

Filtering recursions for calculating likelihoods for queues based on inter-departure time data. - Paul Fearnhead (Stat. Comput., 2004)

Direct simulation for discrete mixture distributions. - Paul Fearnhead (Stat. Comput., 2005)

Exact Bayesian curve fitting and signal segmentation. - Paul Fearnhead (IEEE Trans. Signal Process., 2005)

SequenceLDhot: detecting recombination hotspots. - Paul Fearnhead (Bioinform., 2006)

Exact and efficient Bayesian inference for multiple changepoint problems. - Paul Fearnhead (Stat. Comput., 2006)

Computational methods for complex stochastic systems: a review of some alternatives to MCMC. - Paul Fearnhead (Stat. Comput., 2008)

Editorial: Special issue on adaptive Monte Carlo methods. - Paul Fearnhead (Stat. Comput., 2008)

Efficient Bayesian analysis of multiple changepoint models with dependence across segments. - Paul Fearnhead; Zhen Liu (Stat. Comput., 2011)

Bearings-only tracking with particle filtering for joint parameter learning and state estimation. - Christopher Nemeth; Paul Fearnhead; Lyudmila Mihaylova; Dave Vorley (FUSION, 2012)

Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments. - Christopher Nemeth; Paul Fearnhead; Lyudmila Mihaylova (IEEE Trans. Signal Process., 2014)

On the Identification and Mitigation of Weaknesses in the Knowledge Gradient Policy for Multi-Armed Bandits. - James Edwards; Paul Fearnhead; Kevin D. Glazebrook (CoRR, 2016)

Augmentation schemes for particle MCMC. - Paul Fearnhead; Loukia Meligkotsidou (Stat. Comput., 2016)

A computationally efficient nonparametric approach for changepoint detection. - Kaylea Haynes; Paul Fearnhead; Idris A. Eckley (Stat. Comput., 2017)

On optimal multiple changepoint algorithms for large data. - Robert Maidstone; Toby Hocking; Guillem Rigaill; Paul Fearnhead (Stat. Comput., 2017)

Large-Scale Stochastic Sampling from the Probability Simplex. - Jack Baker; Paul Fearnhead; Emily B. Fox; Christopher Nemeth (NeurIPS, 2018)

A linear time method for the detection of point and collective anomalies. - Alexander Tristan Maximilian Fisch; Idris Arthur Eckley; Paul Fearnhead (CoRR, 2018)

Stochastic Gradient MCMC for Nonlinear State Space Models. - Christopher Aicher; Srshti Putcha; Christopher Nemeth; Paul Fearnhead; Emily B. Fox (CoRR, 2019)

Control variates for stochastic gradient MCMC. - Jack Baker; Paul Fearnhead; Emily B. Fox; Christopher Nemeth (Stat. Comput., 2019)

Most Recent Changepoint Detection in Panel Data. - Lawrence Bardwell; Paul Fearnhead; Idris A. Eckley; Simon Smith; Martin Spott (Technometrics, 2019)

Motor unit number estimation via sequential Monte Carlo. - Simon A. C. Taylor; Chris Sherlock; Gareth Ridall; Paul Fearnhead (Comput. Stat. Data Anal., 2020)

Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data. - Toby Dylan Hocking; Guillem Rigaill; Paul Fearnhead; Guillaume Bourque (J. Mach. Learn. Res., 2020)

BayesProject: Fast computation of a projection direction for multivariate changepoint detection. - Georg Hahn; Paul Fearnhead; Idris A. Eckley (Stat. Comput., 2020)

Semi-automated simultaneous predictor selection for regression-SARIMA models. - Aaron P. Lowther; Paul Fearnhead; Matthew A. Nunes; Kjeld Jensen (Stat. Comput., 2020)

Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes. - Augustin Chevallier; Frédéric Cazals; Paul Fearnhead (AISTATS, 2022)

Continuously Tempered PDMP samplers. - Matthew Sutton; Robert Salomone; Augustin Chevallier; Paul Fearnhead (NeurIPS, 2022)

Automatic Change-Point Detection in Time Series via Deep Learning. - Jie Li; Paul Fearnhead; Piotr Fryzlewicz; Tengyao Wang (CoRR, 2022)

Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data. - Toby Dylan Hocking; Guillem Rigaill; Paul Fearnhead; Guillaume Bourque (J. Stat. Softw., 2022)

Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes. - Fabrizio Laurini; Paul Fearnhead; Jonathan A. Tawn (Stat. Comput., 2022)

A linear time method for the detection of collective and point anomalies. - Alexander Tristan Maximilian Fisch; Idris A. Eckley; Paul Fearnhead (Stat. Anal. Data Min., 2022)

Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle Filter. - Alexander Tristan Maximilian Fisch; Idris A. Eckley; Paul Fearnhead (IEEE Trans. Signal Process., 2022)

Subset Multivariate Collective and Point Anomaly Detection. - Alexander Tristan Maximilian Fisch; Idris A. Eckley; Paul Fearnhead (J. Comput. Graph. Stat., 2022)

Preferential Subsampling for Stochastic Gradient Langevin Dynamics. - Srshti Putcha; Christopher Nemeth; Paul Fearnhead (AISTATS, 2023)

Online non-parametric changepoint detection with application to monitoring operational performance of network devices. - Edward Austin; Gaetano Romano; Idris A. Eckley; Paul Fearnhead (Comput. Stat. Data Anal., 2023)

Concave-Convex PDMP-based Sampling. - Matthew Sutton; Paul Fearnhead (J. Comput. Graph. Stat., 2023)

Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics. - Gaetano Romano; Idris A. Eckley; Paul Fearnhead; Guillem Rigaill (J. Mach. Learn. Res., 2023)

gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection. - Vincent Runge; Toby Dylan Hocking; Gaetano Romano; Fatemeh Afghah; Paul Fearnhead; Guillem Rigaill (J. Stat. Softw., 2023)

Semiparametric detection of changepoints in location, scale, and copula. - Gaurav Agarwal; Idris A. Eckley; Paul Fearnhead (Stat. Anal. Data Min., 2023)

Diffusion Generative Modelling for Divide-and-Conquer MCMC. - C. Trojan; Paul Fearnhead; Christopher Nemeth (CoRR, 2024)

Stochastic Gradient Piecewise Deterministic Monte Carlo Samplers. - Paul Fearnhead; Sebastiano Grazzi; Christopher Nemeth; Gareth O. Roberts (CoRR, 2024)

Scalable Monte Carlo for Bayesian Learning. - Paul Fearnhead; Christopher Nemeth; Chris J. Oates; Chris Sherlock (CoRR, 2024)

cpop: Detecting Changes in Piecewise-Linear Signals. - Paul Fearnhead; Daniel Grose (J. Stat. Softw., 2024)

anomaly: Detection of Anomalous Structure in Time Series Data. - Alexander Tristan Maximilian Fisch; Daniel Grose; Idris A. Eckley; Paul Fearnhead; Lawrence Bardwell (J. Stat. Softw., 2024)

A Log-Linear Nonparametric Online Changepoint Detection Algorithm Based on Functional Pruning. - Gaetano Romano; Idris A. Eckley; Paul Fearnhead (IEEE Trans. Signal Process., 2024)

A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models. - Kes Ward; Gaetano Romano; Idris A. Eckley; Paul Fearnhead (Stat. Comput., 2024)

A communication-efficient, online changepoint detection method for monitoring distributed sensor networks. - Ziyang Yang; Idris A. Eckley; Paul Fearnhead (Stat. Comput., 2024)

Improving power by conditioning on less in post-selection inference for changepoints. - Rachel Carrington; Paul Fearnhead (Stat. Comput., 2025)

Simulation based composite likelihood. - Lorenzo Rimella; Chris Jewell; Paul Fearnhead (Stat. Comput., 2025)