Paul Fearnhead - researchr alias

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Viewing Publication 1 - 41 from 41

2025

Improving power by conditioning on less in post-selection inference for changepointsRachel Carrington, Paul Fearnhead. sac, 35(1):8, February 2025. [doi]

Simulation based composite likelihoodLorenzo Rimella, Chris Jewell, Paul Fearnhead. sac, 35(3):58, June 2025. [doi]

2024

cpop: Detecting Changes in Piecewise-Linear SignalsPaul Fearnhead, Daniel Grose. jstatsoft, 109(7), 2024. [doi]

anomaly: Detection of Anomalous Structure in Time Series DataAlexander Tristan Maximilian Fisch, Daniel Grose, Idris A. Eckley, Paul Fearnhead, Lawrence Bardwell. jstatsoft, 110(1), 2024. [doi]

A Log-Linear Nonparametric Online Changepoint Detection Algorithm Based on Functional PruningGaetano Romano, Idris A. Eckley, Paul Fearnhead. tsp, 72:594-606, 2024. [doi]

A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family modelsKes Ward, Gaetano Romano, Idris A. Eckley, Paul Fearnhead. sac, 34(3):99, June 2024. [doi]

A communication-efficient, online changepoint detection method for monitoring distributed sensor networksZiyang Yang, Idris A. Eckley, Paul Fearnhead. sac, 34(3):115, June 2024. [doi]

2023

Semiparametric detection of changepoints in location, scale, and copulaGaurav Agarwal, Idris A. Eckley, Paul Fearnhead. sadm, 16(5):456-473, October 2023. [doi]

Online non-parametric changepoint detection with application to monitoring operational performance of network devicesEdward Austin, Gaetano Romano, Idris A. Eckley, Paul Fearnhead. csda, 177:107551, 2023. [doi]

Preferential Subsampling for Stochastic Gradient Langevin DynamicsSrshti Putcha, Christopher Nemeth, Paul Fearnhead. aistats 2023: 8837-8856 [doi]

Fast Online Changepoint Detection via Functional Pruning CUSUM StatisticsGaetano Romano, Idris A. Eckley, Paul Fearnhead, Guillem Rigaill. jmlr, 24, 2023. [doi]

R Package for Univariate Graph-Constrained Change-Point DetectionVincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill. jstatsoft, 106(6), 2023. [doi]

Concave-Convex PDMP-based SamplingMatthew Sutton, Paul Fearnhead. jcgs, 32(4):1425-1435, 2023. [doi]

2022

Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov ProcessesAugustin Chevallier, Frédéric Cazals, Paul Fearnhead. aistats 2022: 10146-10160 [doi]

A linear time method for the detection of collective and point anomaliesAlexander Tristan Maximilian Fisch, Idris A. Eckley, Paul Fearnhead. sadm, 15(4):494-508, 2022. [doi]

Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle FilterAlexander Tristan Maximilian Fisch, Idris A. Eckley, Paul Fearnhead. tsp, 70:47-56, 2022. [doi]

Subset Multivariate Collective and Point Anomaly DetectionAlexander Tristan Maximilian Fisch, Idris A. Eckley, Paul Fearnhead. jcgs, 31(1):574-585, January 2022. [doi]

Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic DataToby Dylan Hocking, Guillem Rigaill, Paul Fearnhead, Guillaume Bourque. jstatsoft, 101(10), 2022. [doi]

Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processesFabrizio Laurini, Paul Fearnhead, Jonathan A. Tawn. sac, 32(6):104, 2022. [doi]

Continuously Tempered PDMP samplersMatthew Sutton, Robert Salomone, Augustin Chevallier, Paul Fearnhead. nips 2022: [doi]

2020

2019

Control variates for stochastic gradient MCMCJack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth. sac, 29(3):599-615, 2019. [doi]

Most Recent Changepoint Detection in Panel DataLawrence Bardwell, Paul Fearnhead, Idris A. Eckley, Simon Smith, Martin Spott. technometrics, 61(1):88-98, 2019. [doi]

2018

Large-Scale Stochastic Sampling from the Probability SimplexJack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth. nips 2018: 6722-6732 [doi]

2017

A computationally efficient nonparametric approach for changepoint detectionKaylea Haynes, Paul Fearnhead, Idris A. Eckley. sac, 27(5):1293-1305, 2017. [doi]

On optimal multiple changepoint algorithms for large dataRobert Maidstone, Toby Hocking, Guillem Rigaill, Paul Fearnhead. sac, 27(2):519-533, 2017. [doi]

2016

Augmentation schemes for particle MCMCPaul Fearnhead, Loukia Meligkotsidou. sac, 26(6):1293-1306, 2016. [doi]

2014

Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing EnvironmentsChristopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova. tsp, 62(5):1245-1255, 2014. [doi]

2012

Bearings-only tracking with particle filtering for joint parameter learning and state estimationChristopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova, Dave Vorley. fusion 2012: 824-831 [doi]

2011

Efficient Bayesian analysis of multiple changepoint models with dependence across segmentsPaul Fearnhead, Zhen Liu. sac, 21(2):217-229, 2011. [doi]

2008

Editorial: Special issue on adaptive Monte Carlo methodsPaul Fearnhead. sac, 18(4):341-342, 2008. [doi]

Computational methods for complex stochastic systems: a review of some alternatives to MCMCPaul Fearnhead. sac, 18(2):151-171, 2008. [doi]

2006

SequenceLDhot: detecting recombination hotspotsPaul Fearnhead. bioinformatics, 22(24):3061-3066, 2006. [doi]

Exact and efficient Bayesian inference for multiple changepoint problemsPaul Fearnhead. sac, 16(2):203-213, 2006. [doi]

2005

Direct simulation for discrete mixture distributionsPaul Fearnhead. sac, 15(2):125-133, 2005. [doi]

Exact Bayesian curve fitting and signal segmentationPaul Fearnhead. tsp, 53(6):2160-2166, 2005. [doi]

2004

Filtering recursions for calculating likelihoods for queues based on inter-departure time dataPaul Fearnhead. sac, 14(3):261-266, 2004. [doi]

Particle filters for mixture models with an unknown number of componentsPaul Fearnhead. sac, 14(1):11-21, 2004. [doi]

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