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
Cornish, R., Vanetti, P., Bouchard-Côté, A., Deligiannidis, G. and Doucet, A. (2019) “Scalable Metropolis-Hastings for exact Bayesian inference with large datasets”, in Proceedings of Machine Learning Research. Journal of Machine Learning Research, pp. 1351–1360.
Hayou, S., Doucet, A. and Rousseau, J. (2019) “On the impact of the activation function on deep neural networks training”, in Proceedings of Machine Learning Research. Journal of Machine Learning Research.
Schmon, S., Deligiannidis, G. and Doucet, A. (2019) “Bernoulli race particle filters”, in Proceedings of Machine Learning Research: 22nd International Conference on Artificial Intelligence and Statistics. MLR Press, pp. 2350–2358.
Middleton, L., Deligiannidis, G., Doucet, A. and Jacob, P. (2019) “Unbiased smoothing using Particle Independent Metropolis-Hastings”, in Proceedings of Machine Learning Research: 22nd International Conference on Artificial Intelligence and Statistics. MLR Press, pp. 2378–2387.
Cornish, R., Vanetti, P., Bouchard-Côté, A., Deligiannidis, G. and Doucet, A. (2019) “Scalable metropolis-hastings for exact Bayesian inference with large datasets”, in 36th International Conference on Machine Learning, ICML 2019, pp. 2398–2429.
Maddison, C., Lawson, D., Tucker, G., Heess, N., Doucet, A., Mnih, A. and Teh, Y. (2019) “Particle value functions”, in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings.
Shestopaloff, A. and Doucet, A. (2019) “Replica Conditional Sequential Monte Carlo”, in INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 97.
Maddison, C., Lawson, D., Tucker, G., Heess, N., Doucet, A., Mnih, A. and Teh, Y. (2019) “Particle value functions”, in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings.
Contact Details
College affiliation: Fellow at Hertford College
Telephone: +44(0)1865 285368
Office number: 1.09