Professor François-Xavier Briol
.
| Position | Professor of Statistics and Machine Learning |
| Phone (external) | |
| Phone (internal) | |
| Email(*) | f.briol |
| Personal webpage | https://fxbriol.github.io/ |
| Themes | Computational Statistics and Machine Learning, Environmental Statistics |
* @ucl.ac.uk
Biographical Details
Dr François-Xavier Briol is a Professor in Statistical Science at UCL, where he co-leads the Fundamentals of Statistical Machine Learning research group.
Research Interests
Dr François-Xavier Briol’s research interests span the intersection of computational statistics, machine learning and applied mathematics. His work primarily focuses on methodology for statistical computation and inference for large scale and computationally expensive probabilistic models.
Selected publications
- Dellaporta, C., Knoblauch, J., Damoulas, T., & Briol, F.-X. (2022). Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap. International Conference on Artificial Intelligence and Statistics (AISTATS), 943–970. Received Best Paper Award.
- Matsubara, T., Knoblauch, J., Briol, F.-X., & Oates, C. J. (2022). Robust generalised Bayesian inference for intractable likelihoods. Journal of the Royal Statistical Society B: Statistical Methodology.
- Wynne, G., Briol, F.-X., & Girolami, M. (2021). Convergence guarantees for Gaussian process means with misspecified likelihoods and smoothness. Journal of Machine Learning Research, 22(123), 1–40.
- Briol, F.-X., Oates, C. J., Girolami, M., Osborne, M. A., & Sejdinovic, D. (2019). Probabilistic integration: A role in statistical computation? (with discussion). Statistical Science, 34(1), 1–22.
- Barp, A., Briol, F.-X., Duncan, A. B., Girolami, M., & Mackey, L. (2019). Minimum Stein discrepancy estimators. In Neural Information Processing Systems (pp 12964-12976).