I am currently a third year PhD student supervised by Professor Mark Girolami and am part of a joint PhD program between the statistics departments at the University of Warwick and the University of Oxford (OxWaSP). Since September 2016, I am also a visiting student in the Mathematics Department at Imperial College London.
My main academic interests are at the interface of computational statistics, machine learning and applied mathematics. Most of my work focuses on probabilistic numerical methods and on the particular problem of computing integrals via probabilistic integration. As such, I am part of the 2017-2018 SAMSI working group on probabilistic numerics. You can also see the following page for a summary of some of my research. More recently, I have also been working on Monte Carlo methods, with a special focus on applications of Stein's method and geometry to constructing control variates and Markov Chain Monte Carlo samplers.
NEWS: I will be visiting the Department of Computing and Mathematical Sciences at the California Institute of Technology in August and September 2017.
- Briol, F-X., Oates, C. J., Cockayne, J., Chen, W. Y. & Girolami, M. (2017). On the Sampling Problem for Kernel Quadrature. To appear in the Proceeding of the International Conference On Machine Learning (ICML). [arXiv]
- Barp, A., Briol, F-X., Kennedy, A. D. & Girolami, M. (2017). Geometry and Dynamics for Markov Chain Monte Carlo. arXiv:1705.02891. Accepted for publication in "Annual Review of Statistics and Its Applications".[arXiv] [journal]
- Oates, C. J., Niederer, S., Lee, A., Briol, F-X. & Girolami, M. (2016). Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models. arXiv:1606.06841. [arXiv]
- Oates, C. J., Cockayne, J., Briol, F-X. & Girolami, M. (2016). Convergence Rates for a Class of Estimators Based on Stein's Identity. arXiv:1603.03220. [arXiv]
- Briol, F-X., Oates, C. J., Girolami, M., Osborne, M. A. & Sejdinovic, D. (2015). Probabilistic Integration: A Role for Statisticians in Numerical Analysis? [Student Paper award 2016 from the Section on Bayesian Statistical Science of the ASA] [arXiv] [code] [blog post by A. Gelman] [blog post by C. Robert]
- Briol, F-X., Oates, C. J., Girolami, M. & Osborne, M. A. (2015). Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. Advances In Neural Information Processing Systems (NIPS), pages 1162-1170. [accepted with spotlight presentation (top 4.5% of submitted papers)]. [arXiv] [conference] [blog post by I. Schuster]
- Barp, A., Barp, E. G., Briol, F-X. & Ueltschi, D. (2015). A numerical study of the 3D random interchange and random loop models. Journal of Physics A: Mathematical and Theoretical, 48(34). [journal] [arXiv]
- Briol, F-X. & Girolami, M. (2017). Bayesian Numerical Methods as a Case Study for Statistical Data Science. to appear at "Statistical Data Science". [pdf]
- Briol, F-X., Cockayne, J. & Teymur, O. (2016). Contributed Discussion on Article by Chkrebtii, Campbell, Calderhead, and Girolami. Bayesian Analysis, Vol 11, Num 4, pp1285-1293. [journal] [arXiv]
For more details, see also my Google scholar profile.
Talks & Posters
- 3rd-5th July - Talk - Statistical Data Science Workshop, Imperial College London and Winton Capital (London, UK).
- 10th July 2017 - Talk - SIAM Annual Meeting, Advances for PDE-constrained Bayesian Inverse Problem, David Lawrence Convention Center (Pittsburgh, US).
See the following page for a list of previous talks and posters presented. Slides are available on request.
f-x.briol at warwick.ac.uk
- f.briol16 at ic.ac.uk