Paul Fearnhead

Stat. Comput., June, 2024

A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models.

[BibT_eX]

[DOI]

Stat. Comput., June, 2024

A Log-Linear Nonparametric Online Changepoint Detection Algorithm Based on Functional Pruning.

[BibT_eX]

[DOI]

Gaetano Romano

IEEE Trans. Signal Process., 2024

2023

Semiparametric detection of changepoints in location, scale, and copula.

[BibT_eX]

[DOI]

Gaurav Agarwal

Stat. Anal. Data Min., October, 2023

gfpop: An <i>R</i> Package for Univariate Graph-Constrained Change-Point Detection.

[BibT_eX]

[DOI]

J. Stat. Softw., 2023

Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Online non-parametric changepoint detection with application to monitoring operational performance of network devices.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2023

Preferential Subsampling for Stochastic Gradient Langevin Dynamics.

[BibT_eX]

[DOI]

Srshti Putcha

Christopher Nemeth

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Subset Multivariate Collective and Point Anomaly Detection.

[BibT_eX]

[DOI]

J. Comput. Graph. Stat., January, 2022

Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle Filter.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2022

A linear time method for the detection of collective and point anomalies.

[BibT_eX]

[DOI]

Stat. Anal. Data Min., 2022

Limit theory and robust evaluation methods for the extremal properties of GARCH(p, q) processes.

[BibT_eX]

[DOI]

Fabrizio Laurini

Jonathan A. Tawn

Stat. Comput., 2022

Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data.

[BibT_eX]

[DOI]

J. Stat. Softw., 2022

Automatic Change-Point Detection in Time Series via Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Continuously Tempered PDMP samplers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes.

[BibT_eX]

[DOI]

Augustin Chevallier

Frédéric Cazals

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020

Semi-automated simultaneous predictor selection for regression-SARIMA models.

[BibT_eX]

[DOI]

Stat. Comput., 2020

BayesProject: Fast computation of a projection direction for multivariate changepoint detection.

[BibT_eX]

[DOI]

Georg Hahn

Stat. Comput., 2020

Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Motor unit number estimation via sequential Monte Carlo.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2020

2019

Most Recent Changepoint Detection in Panel Data.

[BibT_eX]

[DOI]

Technometrics, 2019

Control variates for stochastic gradient MCMC.

[BibT_eX]

[DOI]

Stat. Comput., 2019

Stochastic Gradient MCMC for Nonlinear State Space Models.

[BibT_eX]

[DOI]

CoRR, 2019

2018

A linear time method for the detection of point and collective anomalies.

[BibT_eX]

[DOI]

Idris Arthur Eckley

CoRR, 2018

Large-Scale Stochastic Sampling from the Probability Simplex.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

On optimal multiple changepoint algorithms for large data.

[BibT_eX]

[DOI]

Stat. Comput., 2017

A computationally efficient nonparametric approach for changepoint detection.

[BibT_eX]

[DOI]

Kaylea Haynes

Stat. Comput., 2017

2016

Augmentation schemes for particle MCMC.

[BibT_eX]

[DOI]

Loukia Meligkotsidou

Stat. Comput., 2016

On the Identification and Mitigation of Weaknesses in the Knowledge Gradient Policy for Multi-Armed Bandits.

[BibT_eX]

[DOI]

James Edwards

Kevin D. Glazebrook

CoRR, 2016

2014

Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments.

[BibT_eX]

[DOI]

Christopher Nemeth

Lyudmila Mihaylova

IEEE Trans. Signal Process., 2014

2012

Bearings-only tracking with particle filtering for joint parameter learning and state estimation.

[BibT_eX]

[DOI]

Proceedings of the 15th International Conference on Information Fusion, 2012

2011

Efficient Bayesian analysis of multiple changepoint models with dependence across segments.

[BibT_eX]

[DOI]

Zhen Liu

Stat. Comput., 2011

2008

Editorial: Special issue on adaptive Monte Carlo methods.

[BibT_eX]

[DOI]

Stat. Comput., 2008

Computational methods for complex stochastic systems: a review of some alternatives to MCMC.

[BibT_eX]

[DOI]

Stat. Comput., 2008

2006

Exact and efficient Bayesian inference for multiple changepoint problems.

[BibT_eX]

[DOI]

Stat. Comput., 2006

SequenceLDhot: detecting recombination hotspots.

[BibT_eX]

[DOI]

Bioinform., 2006

2005

Exact Bayesian curve fitting and signal segmentation.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2005

Direct simulation for discrete mixture distributions.

[BibT_eX]

[DOI]

Stat. Comput., 2005

2004

Filtering recursions for calculating likelihoods for queues based on inter-departure time data.

[BibT_eX]

[DOI]

Stat. Comput., 2004

Particle filters for mixture models with an unknown number of components.

[BibT_eX]

[DOI]