Breadcrumb
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
Ruiz, F., Titsias, M., Cemgil, T. and Doucet, A. (2021) “Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains”, in 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021, pp. 707–717.
Caterini, A., Cornish, R., Sejdinovic, D. and Doucet, A. (2021) “Variational Inference with Continuously-Indexed Normalizing Flows”, in 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021, pp. 44–53.
Corenflos, A., Thornton, J., Deligiannidis, G. and Doucet, A. (2021) “Differentiable Particle Filtering via Entropy-Regularized Optimal Transport”, in INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139.
Deligiannidis, G., Paulin, D., Bouchard-Côté, A. and Doucet, A. (2020) “Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates”. University of Oxford.
Deligiannidis, G., Paulin, D., Bouchard-Côté, A. and Doucet, A. (2020) “Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates.”
Contact Details
College affiliation: Fellow at Hertford College
Telephone: +44(0)1865 285368
Office number: 1.09