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
Caterini, A., Doucet, A. and Sejdinovic, D. (2019) “Hamiltonian Variational Auto-Encoder”, Advances in Neural Information Processing Systems, 31.
Bǎrbos, A., Caron, F., Giovannelli, J. and Doucet, A. (2018) “Clone MCMC: Parallel high-dimensional Gaussian gibbs sampling”, in Advances in Neural Information Processing Systems 30: 31st Annual Conference on Neural Information Processing Systems (NIPS 2017). Curran Associates, pp. 5021–5029.
Maddison, C., Lawson, D., Tucker, G., Heess, N., Norouzi, M., Mnih, A., Doucet, A. and Teh, Y. (2017) “Filtering variational objectives”, in Advances in Neural Information Processing Systems. Neural Information Processing Systems Foundation.
Bardenet, R., Doucet, A. and Holmes, C. (2017) “On Markov chain Monte Carlo Methods for Tall Data”, Journal of Machine Learning Research, 18(47), pp. 1–43.
Caron, F., Neiswanger, W., Wood, F., Doucet, A. and Davy, M. (2017) “Generalized Polya Urn for Time-Varying Pitman-Yor Processes”, Journal of Machine Learning Research, 18(27), pp. 1–32.
Contact Details
College affiliation: Fellow at Hertford College
Telephone: +44(0)1865 285368
Office number: 1.09