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Particle filters are a powerful and flexible tool for performing inference on state-space models.
On the generalized distance in statistics
Prasanta Chandra Mahalanobis · 1936
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On a least squares adjustment of a sampled frequency table when the expected marginal totals are known
W Edwards Deming and Frederick F Stephan · 1940
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The hungarian method for the assignment problem
Harold W Kuhn · 1955
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On the translocation of masses
Leonid Kantorovitch · 1958
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An algorithm for finding best matches in logarithmic expected time
Jerome H Friedman, Jon Louis Bentley, and Raphael Ari Finkel · 1977
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The rate of convergence of sinkhorn balancing
George W Soules · 1991
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Practical markov chain monte carlo
Charles J Geyer · 1992
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Novel approach to nonlinear/non-gaussian bayesian state estimation
Neil J Gordon, David J Salmond, and Adrian FM Smith · 1993
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Sequential imputations and bayesian missing data problems
Augustine Kong, Jun S Liu, and Wing Hung Wong · 1994
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Monte carlo filter and smoother for non-gaussian nonlinear state space models
Genshiro Kitagawa · 1996
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Linear programming and extensions
George Bernard Dantzig · 1998
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Bayesian Forecasting & Dynamic Models
Jeff Harrison and Mike West · 1999
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Analyses of infectious disease data from household outbreaks by markov chain monte carlo methods
Philip D O’Neill, David J Balding, Niels G Becker, Mervi Eerola, and Denis Mollison · 2000
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Analytical and numerical studies of noise-induced synchronization of chaotic systems
Raúl Toral, Claudio R Mirasso, Emilio Hernández-Garcıa, and Oreste Piro · 2001
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Noise-induced phase synchronization and synchronization transitions in chaotic oscillators
Changsong Zhou and Jürgen Kurths · 2002
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On building fast kd-trees for ray tracing, and on doing that in o (n log n)
Ingo Wald and Vlastimil Havran · 2006
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Stochastic simulation of chemical kinetics
Daniel T Gillespie · 2007
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A second course in probability
Sheldon M Ross and Erol A Peköz · 2007
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Multilevel monte carlo path simulation
Michael B Giles · 2008
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Inapparent infections and cholera dynamics
Aaron A King, Edward L Ionides, Mercedes Pascual, and Menno J Bouma · 2008
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The sinkhorn-knopp algorithm: Convergence and applications
Philip A Knight · 2008
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Locality-sensitive hashing for finding nearest neighbors [lecture notes]
Malcolm Slaney and Michael Casey · 2008
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The pseudo-marginal approach for efficient monte carlo computations
Christophe Andrieu and Gareth O Roberts · 2009
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Inference in hidden markov models, 2009
Olivier Cappé, Eric Moulines, and Tobias Rydén · 2009
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A tutorial on particle filtering and smoothing: Fifteen years later
Arnaud Doucet and Adam M Johansen · 2009
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Optimal filtering of jump diffusions: Extracting latent states from asset prices
Michael S Johannes, Nicholas G Polson, and Jonathan R Stroud · 2009
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Monte carlo inference for state–space models of wild animal populations
Ken B Newman, Carmen Fernández, Len Thomas, and Stephen T Buckland · 2009
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Fast and robust earth mover’s distances
Ofir Pele and Michael Werman · 2009
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Convergence properties of pseudo-marginal markov chain monte carlo algorithms
Christophe Andrieu, Matti Vihola, et al · 2015
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Multilevel sequential monte carlo samplers
Alexandros Beskos, Ajay Jasra, Kody Law, Raul Tempone, and Yan Zhou · 2015
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On particle gibbs sampling
Nicolas Chopin, Sumeetpal S Singh, et al · 2015
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The correlated pseudo-marginal method
George Deligiannidis, Arnaud Doucet, Michael K Pitt, and Robert Kohn · 2015
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Efficient implementation of markov chain monte carlo when using an unbiased likelihood estimator
Arnaud Doucet, MK Pitt, George Deligiannidis, and Robert Kohn · 2015
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Particle markov chain monte carlo methods
Christophe Andrieu, Arnaud Doucet, and Roman Holenstein · 2010
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Statistical inference for noisy nonlinear ecological dynamic systems
Simon N Wood · 2010
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Bayesian parameter inference for stochastic biochemical network models using particle markov chain monte carlo
Andrew Golightly and Darren J Wilkinson · 2011
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Iterated filtering
Edward L Ionides, Anindya Bhadra, Yves Atchadé, Aaron King, et al · 2011
Cited alongside, same era.
Particle approximations of the score and observed information matrix in state space models with application to parameter estimation
George Poyiadjis, Arnaud Doucet, and Sumeetpal S Singh · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Using noise to speed up markov chain monte carlo estimation
Brandon Franzke and Bart Kosko · 2015
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Multilevel monte carlo methods
Michael B Giles · 2015
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Multilevel ensemble kalman filtering
Håkon Hoel, Kody JH Law, and Raul Tempone · 2015
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Ultrasonic tracking of shear waves using a particle filter
Atul N Ingle, Chi Ma, and Tomy Varghese · 2015
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Ajay Jasra, Kengo Kamatani, Kody JH Law, and Yan Zhou · 2015
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On particle methods for parameter estimation in state-space models
Nikolas Kantas, Arnaud Doucet, Sumeetpal S Singh, Jan Maciejowski, Nicolas Chopin, et al · 2015
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Stability of noisy metropolis–hastings
Felipe J Medina-Aguayo, Anthony Lee, and Gareth O Roberts · 2015
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Permutation search methods are efficient, yet faster search is possible
Bilegsaikhan Naidan, Leonid Boytsov, and Eric Nyberg · 2015
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A sparse multi-scale algorithm for dense optimal transport
Bernhard Schmitzer · 2015
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On the efficiency of pseudo-marginal random walk metropolis algorithms
Chris Sherlock, Alexandre H Thiery, Gareth O Roberts, Jeffrey S Rosenthal, et al · 2015
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Data-driven optimal transport
Giulio Trigila and Esteban G Tabak · 2015
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Intelligent particle filter and its application to fault detection of nonlinear system
Shen Yin and Xiangping Zhu · 2015
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Noisy monte carlo: Convergence of markov chains with approximate transition kernels
Pierre Alquier, Nial Friel, Richard Everitt, and Aidan Boland · 2016
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Multilevel sequential monte carlo samplers for normalizing constants
Pierre Del Moral, Ajay Jasra, Kody Law, and Yan Zhou · 2016
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Multilevel ensemble transform particle filtering
Alastair Gregory, CJ Cotter, and Sebastian Reich · 2016
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Multilevel particle filters: Normalizing constant estimation
Ajay Jasra, Kengo Kamatani, Prince Prepah Osei, and Yan Zhou · 2016
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Pierre E Jacob, Fredrik Lindsten, and Thomas B Schön · 2016
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