Sequential Monte Carlo smoothing with application to parameter estimation in nonlinear state space models J Olsson, O Cappé, R Douc, E Moulines Bernoulli 14 (1), 155-179, 2008 | 175 | 2008 |

Sequential Monte Carlo smoothing for general state space hidden Markov models R Douc, A Garivier, E Moulines, J Olsson The Annals of Applied Probability 21 (6), 2109-2145, 2011 | 150 | 2011 |

Consistency of the maximum likelihood estimator for general hidden Markov models R Douc, E Moulines, J Olsson, R Van Handel the Annals of Statistics 39 (1), 474-513, 2011 | 105 | 2011 |

Adaptive methods for sequential importance sampling with application to state space models J Cornebise, É Moulines, J Olsson Statistics and Computing 18 (4), 461-480, 2008 | 84 | 2008 |

Optimality of the auxiliary particle filter R Douc, E Moulines, J Olsson | 63 | 2009 |

Long-term stability of sequential Monte Carlo methods under verifiable conditions R Douc, E Moulines, J Olsson The Annals of Applied Probability 24 (5), 1767-1802, 2014 | 48 | 2014 |

Efficient particle-based online smoothing in general hidden Markov models: the PaRIS algorithm J Olsson, J Westerborn Bernoulli 23 (3), 1951-1996, 2017 | 41 | 2017 |

Rao-Blackwellization of particle Markov chain Monte Carlo methods using forward filtering backward sampling J Olsson, T Ryden IEEE Transactions on Signal Processing 59 (10), 4606-4619, 2011 | 40 | 2011 |

Asymptotic properties of particle filter-based maximum likelihood estimators for state space models J Olsson, T Rydén Stochastic Processes and their Applications 118 (4), 649-680, 2008 | 31 | 2008 |

On the forward filtering backward smoothing particle approximations of the smoothing distribution in general state spaces models R Douc, A Garivier, E Moulines, J Olsson arXiv preprint arXiv:0904.0316, 2009 | 26 | 2009 |

Comparison of asymptotic variances of inhomogeneous Markov chains with application to Markov chain Monte Carlo methods F Maire, R Douc, J Olsson The Annals of Statistics 42 (4), 1483-1510, 2014 | 22 | 2014 |

An explicit variance reduction expression for the Rao-Blackwellised particle filter F Lindsten, TB Schön, J Olsson IFAC Proceedings Volumes 44 (1), 11979-11984, 2011 | 19 | 2011 |

Convergence properties of weighted particle islands with application to the double bootstrap algorithm P Del Moral, E Moulines, J Olsson, C Vergé arXiv preprint arXiv:1410.4231, 2014 | 18 | 2014 |

Numerically stable online estimation of variance in particle filters J Olsson, R Douc Bernoulli 25 (2), 1504-1535, 2019 | 13 | 2019 |

Adaptive sequential Monte Carlo by means of mixture of experts J Cornebise, E Moulines, J Olsson Statistics and Computing 24 (3), 317-337, 2014 | 12 | 2014 |

Particle-based likelihood inference in partially observed diffusion processes using generalised Poisson estimators J Olsson, J Ströjby Electronic Journal of Statistics 5, 1090-1122, 2011 | 11 | 2011 |

Efficient particle-based online smoothing in general hidden Markov models J Westerborn, J Olsson 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 10 | 2014 |

Posterior consistency for partially observed Markov models R Douc, J Olsson, F Roueff arXiv preprint arXiv:1608.06851, 2016 | 8* | 2016 |

Particle-based online estimation of tangent filters with application to parameter estimation in nonlinear state-space models J Olsson, JW Alenlöv Annals of the Institute of Statistical Mathematics 72 (2), 545-576, 2020 | 6 | 2020 |

On the auxiliary particle filter R Douc, E Moulines, J Olsson arXiv preprint arXiv:0709.3448, 2007 | 6 | 2007 |