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
Thin, A., Janati, Y., Le Corff, S., Ollion, C., Doucet, A., Durmus, A., Moulines, E. and Robert, C. (2022) “NEO: non equilibrium sampling on the orbits of a deterministic transform”, in Advances in Neural Information Processing Systems 34 (NeurIPS 2021). Curran Associates, pp. 17060–17071.
De Bortoli, V., Thornton, J., Heng, J. and Doucet, A. (2022) “Diffusion Schrödinger bridge with applications to score-based generative modeling”, in Advances in Neural Information Processing Systems 34 (NeurIPS 2021). Curran Associates, pp. 17695–17709.
Clerico, E., Deligiannidis, G. and Doucet, A. (2022) “Conditionally Gaussian PAC-Bayes”, in. Journal of Machine Learning Research, pp. 2311–2329.
Dupont, E., Teh, Y. and Doucet, A. (2022) “Generative models as distributions of functions”, in. Journal of Machine Learning Research, pp. 2989–3015.
Vono, M., Paulin, D. and Doucet, A. (2022) “Efficient MCMC sampling with dimension-free convergence rate using ADMM-type splitting”, Journal of Machine Learning Research, 23(25), pp. 1–69.
Stutz, D., Dvijotham, K., Cemgil, A. and Doucet, A. (2022) “LEARNING OPTIMAL CONFORMAL CLASSIFIERS”, in ICLR 2022 - 10th International Conference on Learning Representations.
Contact Details
College affiliation: Fellow at Hertford College
Telephone: +44(0)1865 285368
Office number: 1.09