| Sequential Monte Carlo Methods in Practice A Doucet, N De Freitas, N Gordon Sequential monte carlo methods in practice, 2001 | 11051 | 2001 |
| On sequential Monte Carlo sampling methods for Bayesian filtering A Doucet, S Godsill, C Andrieu Statistics and computing 10 (3), 197-208, 2000 | 6837 | 2000 |
| An introduction to MCMC for machine learning C Andrieu, N De Freitas, A Doucet, MI Jordan Machine learning 50 (1), 5-43, 2003 | 3917 | 2003 |
| A tutorial on particle filtering and smoothing: Fifteen years later A Doucet, AM Johansen Oxford Handbook of Nonlinear Filtering 12 (656-704), 3, 2011 | 3042* | 2011 |
| Particle Markov chain Monte Carlo methods C Andrieu, A Doucet, R Holenstein Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010 | 2920 | 2010 |
| The unscented particle filter R Van Der Merwe, A Doucet, N De Freitas, EA Wan Advances in Neural Information Processing Systems, 2000 | 2715 | 2000 |
| Sequential Monte Carlo samplers P Del Moral, A Doucet, A Jasra Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006 | 2518 | 2006 |
| Rao-Blackwellised particle filtering for dynamic Bayesian networks A Doucet, N De Freitas, K Murphy, S Russell UAI 2000, 2000 | 2182* | 2000 |
| An introduction to sequential Monte Carlo methods A Doucet, N De Freitas, N Gordon Sequential Monte Carlo methods in practice, 3-14, 2001 | 1866 | 2001 |
| Sequential Monte Carlo methods for multitarget filtering with random finite sets BN Vo, S Singh, A Doucet IEEE Transactions on Aerospace and electronic systems 41 (4), 1224-1245, 2005 | 1713 | 2005 |
| A survey of convergence results on particle filtering methods for practitioners D Crisan, A Doucet IEEE Transactions on signal processing 50 (3), 736-746, 2002 | 1429 | 2002 |
| Particle filters for state estimation of jump Markov linear systems A Doucet, NJ Gordon, V Krishnamurthy IEEE Transactions on signal processing 49 (3), 613-624, 2002 | 1162 | 2002 |
| On sequential simulation-based methods for Bayesian filtering A Doucet Technical Report CUED/F-INFENG/TR.310 Cambridge University, 1998 | 1079 | 1998 |
| Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the 31st International Conference on Machine Learning, 685-693, 2014 | 1036 | 2014 |
| Augmented neural ODEs E Dupont, A Doucet, Y Teh Advances in Neural Information Processing Systems 32 (NIPS 2019) 32 (2019), 2019 | 944 | 2019 |
| Monte Carlo smoothing for nonlinear time series SJ Godsill, A Doucet, M West Journal of the american statistical association, 2004 | 779 | 2004 |
| Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling V De Bortoli, J Thornton, J Heng, A Doucet NeurIPS 2021, 2021 | 738 | 2021 |
| An adaptive sequential Monte Carlo method for approximate Bayesian computation P Del Moral, A Doucet, A Jasra Statistics and computing 22 (5), 1009-1020, 2012 | 684 | 2012 |
| On particle methods for parameter estimation in state-space models N Kantas, A Doucet, SS Singh, JM Maciejowski, N Chopin Statistical Science 30 (3), 328--351, 2015 | 653 | 2015 |
| Maintaining multi-modality through mixture tracking J Vermaak, A Doucet, P Patrick International Conference on Computer Vision, 1110, 2003 | 563 | 2003 |
Christophe AndrieuProfessor of Statistics, University of BristolVerified email at bristol.ac.uk
