selected publications

• academic article

  • A pseudo-marginal sequential Monte Carlo online smoothing algorithm.  Bernoulli.  28. 2022
  • Posterior consistency for partially observed Markov models.  Stochastic Processes and their Applications.  130:733-759. 2019
  • On the use of Markov chain Monte Carlo methods for the sampling of mixture models: a statistical perspective.  Statistics and Computing.  25:95-110. 2014
  • Long-term stability of sequential Monte Carlo methods under verifiable conditions.  The Annals of Applied Probability.  24. 2014
  • On the long-term stability of bootstrap-type particle filters.  IFAC Proceedings Volumes.  45:1131-1136. 2012
  • Sequential Monte Carlo smoothing for general state space hidden Markov models.  The Annals of Applied Probability.  21. 2011
  • Consistency of the maximum likelihood estimator for general hidden Markov models.  The Annals of Statistics.  39. 2011
  • Optimality of the auxiliary particle filter.  .  2009

• blog posting

  • State and parameter learning with PaRIS particle Gibbs.  arXiv (Cornell University). 2023
  • Backward importance sampling for partially observed diffusion processes.  HAL (Le Centre pour la Communication Scientifique Directe). 2020
  • Online pseudo Marginal Sequential Monte Carlo smoother for general state spaces. Application to recursive maximum likelihood estimation of stochastic differential equations.  HAL (Le Centre pour la Communication Scientifique Directe). 2019
  • On the Forward Filtering Backward Smoothing particle approximations of the smoothing distribution in general state spaces models.  arXiv (Cornell University). 2009