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

Crucinio, F., Doucet, A. and Johansen, A. (2021) “A particle method for solving Fredholm equations of the first kind”, Journal of the American Statistical Association, 118(542), pp. 937–947.
Deligiannidis, G., Bortoli, V. and Doucet, A. (2021) “Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure.”
Thin, A., Kotelevskii, N., Durmus, A., Panov, M., Moulines, E. and Doucet, A. (2021) “Monte Carlo variational auto-encoders”, in. Journal of Machine Learning Research, pp. 7258–7267.
Ruan, Y., Ullrich, K., Severo, D., Townsend, J., Khisti, A., Doucet, A., Makhzani, A. and Maddison, C. (2021) “Improving lossless compression rates via Monte Carlo bits-back coding”, in. Journal of Machine Learning Research, pp. 9136–9147.
Arbel, M., Matthews, A. and Doucet, A. (2021) “Annealed Flow Transport Monte Carlo”, in. Journal of Machine Learning Research, pp. 318–330.
Corenflos, A., Thornton, J., Deligiannidis, G. and Doucet, A. (2021) “Differentiable particle filtering via entropy-regularized optimal transport”, in. Journal of Machine Learning Research, pp. 2100–2111.
Alenlov, J., Doucet, A. and Lindsten, F. (2021) “Pseudo-marginal Hamiltonian Monte Carlo”, Journal of Machine Learning Research, 22(141), pp. 1–45.
Maddison, C., Paulin, D., Teh, Y. and Doucet, A. (2021) “Dual space preconditioning for gradient descent”, SIAM Journal on Optimization, 31(1), pp. 991–1016.
Hayou, S., Clerico, E., He, B., Deligiannidis, G., Doucet, A. and Rousseau, J. (2021) “Stable ResNet”, in Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. Journal of Machine Learning Research, pp. 1324–1332.
Tadic, V. and Doucet, A. (2021) “Bias of particle approximations to optimal filter derivative”, SIAM Journal on Control and Optimization, 59(1), pp. 727–748.

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