Paul Fearnhead

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 38

Top Topics

Monte Carlo Methods

Detection Algorithm

Top Venues

J. Stat. Softw.

IEEE Trans. Signal Process.

Publications

Gaetano Romano, Idris A. Eckley, Paul Fearnhead
A Log-Linear Nonparametric Online Changepoint Detection Algorithm Based on Functional Pruning. IEEE Trans. Signal Process. 72 (2024)
Kes Ward, Gaetano Romano, Idris A. Eckley, Paul Fearnhead
A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models. Stat. Comput. 34 (3) (2024)
Paul Fearnhead, Daniel Grose
cpop: Detecting Changes in Piecewise-Linear Signals. J. Stat. Softw. 109 (7) (2024)
Paul Fearnhead, Sebastiano Grazzi, Christopher Nemeth, Gareth O. Roberts
Stochastic Gradient Piecewise Deterministic Monte Carlo Samplers. CoRR (2024)
Ziyang Yang, Idris A. Eckley, Paul Fearnhead
A communication-efficient, online changepoint detection method for monitoring distributed sensor networks. Stat. Comput. 34 (3) (2024)
Paul Fearnhead, Christopher Nemeth, Chris J. Oates, Chris Sherlock
Scalable Monte Carlo for Bayesian Learning. CoRR (2024)
C. Trojan, Paul Fearnhead, Christopher Nemeth
Diffusion Generative Modelling for Divide-and-Conquer MCMC. CoRR (2024)
Gaurav Agarwal, Idris A. Eckley, Paul Fearnhead
Semiparametric detection of changepoints in location, scale, and copula. Stat. Anal. Data Min. 16 (5) (2023)
Edward Austin, Gaetano Romano, Idris A. Eckley, Paul Fearnhead
Online non-parametric changepoint detection with application to monitoring operational performance of network devices. Comput. Stat. Data Anal. 177 (2023)
Srshti Putcha, Christopher Nemeth, Paul Fearnhead
Preferential Subsampling for Stochastic Gradient Langevin Dynamics. AISTATS (2023)
Vincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill
Package for Univariate Graph-Constrained Change-Point Detection. J. Stat. Softw. 106 (6) (2023)
Matthew Sutton, Paul Fearnhead
Concave-Convex PDMP-based Sampling. J. Comput. Graph. Stat. 32 (4) (2023)
Gaetano Romano, Idris A. Eckley, Paul Fearnhead, Guillem Rigaill
Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics. J. Mach. Learn. Res. 24 (2023)
Srshti Putcha, Christopher Nemeth, Paul Fearnhead
Preferential Subsampling for Stochastic Gradient Langevin Dynamics. CoRR (2022)
Alexander Tristan Maximilian Fisch, Idris A. Eckley, Paul Fearnhead
Subset Multivariate Collective and Point Anomaly Detection. J. Comput. Graph. Stat. 31 (1) (2022)
Jie Li, Paul Fearnhead, Piotr Fryzlewicz, Tengyao Wang
Automatic Change-Point Detection in Time Series via Deep Learning. CoRR (2022)
Alexander Tristan Maximilian Fisch, Idris A. Eckley, Paul Fearnhead
Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle Filter. IEEE Trans. Signal Process. 70 (2022)
Augustin Chevallier, Frédéric Cazals, Paul Fearnhead
Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes. AISTATS (2022)
Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead, Guillaume Bourque
Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data. J. Stat. Softw. 101 (10) (2022)
Fabrizio Laurini, Paul Fearnhead, Jonathan A. Tawn
Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes. Stat. Comput. 32 (6) (2022)
Matthew Sutton, Robert Salomone, Augustin Chevallier, Paul Fearnhead
Continuously Tempered PDMP samplers. NeurIPS (2022)
Alexander Tristan Maximilian Fisch, Idris A. Eckley, Paul Fearnhead
A linear time method for the detection of collective and point anomalies. Stat. Anal. Data Min. 15 (4) (2022)
Augustin Chevallier, Frédéric Cazals, Paul Fearnhead
Efficient computation of the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes. CoRR (2022)
Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead, Guillaume Bourque
Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data. J. Mach. Learn. Res. 21 (2020)
Simon A. C. Taylor, Chris Sherlock, Gareth Ridall, Paul Fearnhead
Motor unit number estimation via sequential Monte Carlo. Comput. Stat. Data Anal. 144 (2020)
Aaron P. Lowther, Paul Fearnhead, Matthew A. Nunes, Kjeld Jensen
Semi-automated simultaneous predictor selection for regression-SARIMA models. Stat. Comput. 30 (6) (2020)
Georg Hahn, Paul Fearnhead, Idris A. Eckley
BayesProject: Fast computation of a projection direction for multivariate changepoint detection. Stat. Comput. 30 (6) (2020)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Control variates for stochastic gradient MCMC. Stat. Comput. 29 (3) (2019)
Lawrence Bardwell, Paul Fearnhead, Idris A. Eckley, Simon Smith, Martin Spott
Most Recent Changepoint Detection in Panel Data. Technometrics 61 (1) (2019)
Christopher Aicher, Srshti Putcha, Christopher Nemeth, Paul Fearnhead, Emily B. Fox
Stochastic Gradient MCMC for Nonlinear State Space Models. CoRR (2019)
Alexander Tristan Maximilian Fisch, Idris Arthur Eckley, Paul Fearnhead
A linear time method for the detection of point and collective anomalies. CoRR (2018)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Large-Scale Stochastic Sampling from the Probability Simplex. CoRR (2018)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Large-Scale Stochastic Sampling from the Probability Simplex. NeurIPS (2018)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Control Variates for Stochastic Gradient MCMC. CoRR (2017)
Robert Maidstone, Toby Hocking, Guillem Rigaill, Paul Fearnhead
On optimal multiple changepoint algorithms for large data. Stat. Comput. 27 (2) (2017)
Kaylea Haynes, Paul Fearnhead, Idris A. Eckley
A computationally efficient nonparametric approach for changepoint detection. Stat. Comput. 27 (5) (2017)
James Edwards, Paul Fearnhead, Kevin D. Glazebrook
On the Identification and Mitigation of Weaknesses in the Knowledge Gradient Policy for Multi-Armed Bandits. CoRR (2016)
Paul Fearnhead, Loukia Meligkotsidou
Augmentation schemes for particle MCMC. Stat. Comput. 26 (6) (2016)
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova
Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments. IEEE Trans. Signal Process. 62 (5) (2014)
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova, Dave Vorley
Bearings-only tracking with particle filtering for joint parameter learning and state estimation. FUSION (2012)
Paul Fearnhead, Zhen Liu
Efficient Bayesian analysis of multiple changepoint models with dependence across segments. Stat. Comput. 21 (2) (2011)
Paul Fearnhead
Editorial: Special issue on adaptive Monte Carlo methods. Stat. Comput. 18 (4) (2008)
Paul Fearnhead
Computational methods for complex stochastic systems: a review of some alternatives to MCMC. Stat. Comput. 18 (2) (2008)
Paul Fearnhead
Exact and efficient Bayesian inference for multiple changepoint problems. Stat. Comput. 16 (2) (2006)
Paul Fearnhead
SequenceLDhot: detecting recombination hotspots. Bioinform. 22 (24) (2006)
Paul Fearnhead
Direct simulation for discrete mixture distributions. Stat. Comput. 15 (2) (2005)
Paul Fearnhead
Exact Bayesian curve fitting and signal segmentation. IEEE Trans. Signal Process. 53 (6) (2005)
Paul Fearnhead
Filtering recursions for calculating likelihoods for queues based on inter-departure time data. Stat. Comput. 14 (3) (2004)
Paul Fearnhead
Particle filters for mixture models with an unknown number of components. Stat. Comput. 14 (1) (2004)