| Sequential Monte Carlo smoothing with application to parameter estimation in nonlinear state space models J Olsson, O Cappé, R Douc, E Moulines | 212 | 2008 |
| Sequential Monte Carlo smoothing for general state space hidden Markov models R Douc, A Garivier, E Moulines, J Olsson | 200 | 2011 |
| Consistency of the maximum likelihood estimator for general hidden Markov models R Douc, E Moulines, J Olsson, R Van Handel | 149 | 2011 |
| Adaptive methods for sequential importance sampling with application to state space models J Cornebise, É Moulines, J Olsson Statistics and Computing 18, 461-480, 2008 | 102 | 2008 |
| Efficient particle-based online smoothing in general hidden Markov models: The PaRIS algorithm J Olsson, J Westerborn | 76 | 2017 |
| Optimality of the auxiliary particle filter R Douc, E Moulines, J Olsson Probability and Mathematical Statistics 29 (1), 1-28, 2009 | 72 | 2009 |
| Long-term stability of sequential Monte Carlo methods under verifiable conditions R Douc, E Moulines, J Olsson | 52 | 2014 |
| 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 | 45 | 2011 |
| Numerically stable online estimation of variance in particle filters J Olsson, R Douc | 34 | 2019 |
| 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 | 34 | 2008 |
| Comparison of asymptotic variances of inhomogeneous Markov chains with application to Markov chain Monte Carlo methods F Maire, R Douc, J Olsson | 30 | 2014 |
| 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 | 28 | 2009 |
| 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 | 23 | 2011 |
| Convergence properties of weighted particle islands with application to the double bootstrap algorithm P Del Moral, E Moulines, J Olsson, C Vergé Stochastic Systems 6 (2), 367-419, 2017 | 22 | 2017 |
| Particle-based likelihood inference in partially observed diffusion processes using generalised Poisson estimators J Olsson, J Ströjby | 20 | 2011 |
| Adaptive sequential Monte Carlo by means of mixture of experts J Cornebise, E Moulines, J Olsson Statistics and Computing 24, 317-337, 2014 | 17 | 2014 |
| A pseudo-marginal sequential Monte Carlo online smoothing algorithm P Gloaguen, S Le Corff, J Olsson Bernoulli 28 (4), 2606-2633, 2022 | 16 | 2022 |
| Probabilistic feature extraction, dose statistic prediction and dose mimicking for automated radiation therapy treatment planning T Zhang, R Bokrantz, J Olsson Medical Physics 48 (9), 4730-4742, 2021 | 16 | 2021 |
| Particle-based online estimation of tangent filters with application to parameter estimation in nonlinear state-space models J Olsson, J Westerborn Alenlöv Annals of the Institute of Statistical Mathematics 72, 545-576, 2020 | 14 | 2020 |
| Posterior consistency for partially observed Markov models R Douc, J Olsson, F Roueff Stochastic Processes and their Applications 130 (2), 733-759, 2020 | 14* | 2020 |
