Professor Arnaud Doucet

Professor of Statistics

Biographical Sketch

I obtained my PhD from the University of Paris XI (Orsay) in 1997. I previously held academic positions at Cambridge University, Melbourne University, The Institute of Statistical Mathematics in Tokyo and the University of British Columbia where I was a Canada Research Chair in Stochastic Computation.

Research Interests

  • Bayesian statistics
  • Stochastic simulations
  • Sequential Monte Carlo
  • Markov chain Monte Carlo
  • Time series

I am primarily interested in the development and study of novel Monte Carlo methods for inference in complex stochastic models.

Publications

Bouchard-Côté, A., Doucet, A. and Roth, A. (2017) “Particle Gibbs split-merge sampling for Bayesian inference in mixture models”, Journal of Machine Learning Research, 18(28), p. 1−39.
Doucet, A., Rainforth, T., Naesseth, C., Lindsten, F., Paige, B., Wood, F. and van de Meent, J.-W. (2016) “Interacting particle Markov chain Monte Carlo”, in ICML 2016: 33rd International Conference on Machine Learning. Journal of Machine Learning Research.
Wang, L., Bouchard-Côté, A. and Doucet, A. (2015) “Bayesian Phylogenetic Inference Using a Combinatorial Sequential Monte Carlo Method”, Journal of the American Statistical Association, 110(512), pp. 1362–1374.
Doucet, A., Pitt, M., Deligiannidis, G. and Kohn, R. (2015) “Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator”, Biometrika, 102(2), pp. 295–313.
Lienart, T., Teh, Y. and Doucet, A. (2015) “Expectation Particle Belief Propagation”, in ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 28 (NIPS 2015).
Del Moral, P., Doucet, A. and Singh, S. (2015) “UNIFORM STABILITY OF A PARTICLE APPROXIMATION OF THE OPTIMAL FILTER DERIVATIVE”, SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 53(3), pp. 1278–1304.
Kantas, N., Doucet, A., Singh, S., Maciejowski, J. and Chopin, N. (2015) “On Particle Methods for Parameter Estimation in State-Space Models”, Statistical Science, 30(3), pp. 328–351.
Cuturi, M. and Doucet, A. (2014) “Fast computation of Wasserstein barycenters”, in Proceedings of Machine Learning Research. Journal of Machine Learning Research, pp. 685–693.
Bishop, A. and Doucet, A. (2014) “Distributed Nonlinear Consensus in the Space of Probability Measures”, in IFAC PAPERSONLINE, pp. 8662–8668.
Bardenet, R., Doucet, A. and Holmes, C. (2014) “Towards scaling up Markov chain Monte Carlo: An adaptive subsampling approach”, in 31st International Conference on Machine Learning, ICML 2014, pp. 630–653.

Contact Details

College affiliation: Fellow at Hertford College

Email:  doucet@stats.ox.ac.uk

Telephone: +44(0)1865 285368

Office number: 1.09

PA:  Lauren Haynes

Graduate Students

Joe Benton

Andrew Campbell

Amitis Shidani

Eugenio Clerico

Guneet Singh Dhillon

Research Groups

Computational Statistics and Machine Learning

Statistical Theory and Methodology