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Bayesian online changepoint detection (BOCPD) (Adams & MacKay, 2007) offers a rigorous and viable way to identify changepoints in complex systems.
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Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Yosihiko Ogata · 1998
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Damien Francois, Vincent Wertz and Michel Verleysen · 2005
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“Bayesian online changepoint detection”
Ryan Adams and David MacKay · 2007
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“On-line inference for multiple changepoint problems”
Paul Fearnhead and Zhen Liu · 2007
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Arnaud Doucet and Adam Johansen · 2009
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“Sequential Bayesian prediction in the presence of changepoints”
Roman Garnett, Michael Osborne and Stephen Roberts · 2009
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“Adaptive sequential Bayesian change point detection”
Ryan Turner, Yunus Saatci and Carl Rasmussen · 2009
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“Gaussian process change point models”
Yunus Saatçi, Ryan Turner and Carl Rasmussen · 2010
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“Bayesian online learning of the hazard rate in change-point problems”
Robert Wilson, Matthew Nassar and Joshua Gold · 2010
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“Multivariate Hawkes processes: an application to financial data”
Paul Embrechts, Thomas Liniger and Lu Lin · 2011
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“On-line changepoint detection and parameter estimation with application to genomic data”
François Caron, Arnaud Doucet and Raphael Gottardo · 2012
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Erik Lewis, George Mohler, P Brantingham and Andrea Bertozzi · 2012
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Angelos Dassios and Hongbiao Zhao · 2013
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“Change-point detection in time-series data by relative density-ratio estimation”
Song Liu, Makoto Yamada, Nigel Collier and Masashi Sugiyama · 2013
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“Online variational approximations to non-exponential family change point models: with application to radar tracking”
“Sequential importance sampling for online Bayesian changepoint detection”
Lida Mavrogonatou and Vladislav Vyshemirsky · 2016
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“Bayesian recurrent neural networks”
Meire Fortunato, Charles Blundell and Oriol Vinyals · 2017
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“Adaptive sequential Monte Carlo for multiple changepoint analysis”
Nicholas Heard and Melissa Turcotte · 2017
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“Detecting changes in dynamic events over networks”
Shuang Li et al · 2017
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“Stein variational gradient descent as gradient flow”
Qiang Liu · 2017
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“Statistical Modelling of Computer Network Traffic Event Times”
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Ryan Turner, Steven Bottone and Clay Stanek · 2013
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“Learning social infectivity in sparse low-rank networks using multi-dimensional Hawkes processes”
Ke Zhou, Hongyuan Zha and Le Song · 2013
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“Hawkes processes in finance”
Emmanuel Bacry, Iacopo Mastromatteo and Jean-François Muzy · 2015
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“Online Bayesian changepoint detection for articulated motion models”
Scott Niekum, Sarah Osentoski, Christopher Atkeson and Andrew Barto · 2015
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“Robust online time series prediction with recurrent neural networks”
Tian Guo et al · 2016
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“Stein variational gradient descent: A general purpose Bayesian inference algorithm”
Qiang Liu and Dilin Wang · 2016
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Matthew Price-Williams and Nick Heard · 2017
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“A Tutorial on Hawkes Processes for Events in Social Media”
Marian-Andrei Rizoiu, Young Lee, Swapnil Mishra and Lexing Xie · 2017
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Jos van Westhuizen and Joan Lasenby · 2017
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“A Stein variational Newton method”
Gianluca Detommaso et al · 2018
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“Lecture Notes: Temporal Point Processes and the Conditional Intensity Function”
Jakob Rasmussen · 2018
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“A review of self-exciting spatio-temporal point processes and their applications”
Alex Reinhart · 2018
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