Следене
François-Xavier Briol
François-Xavier Briol
Associate Professor in Statistical Science, UCL
Потвърден имейл адрес: ucl.ac.uk - Начална страница
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Позовавания
Позовавания
Година
Probabilistic integration: A role in statistical computation? (with discussion)
FX Briol, CJ Oates, M Girolami, M Osborne, D Sejdinovic
Statistical Science 34 (1), 1-22, 2019
218*2019
Stein points
WY Chen, L Mackey, J Gorham, FX Briol, CJ Oates
International Conference on Machine Learning, PMLR, 844-853, 2018
1122018
Minimum Stein discrepancy estimators
A Barp, FX Briol, AB Duncan, M Girolami, L Mackey
Advances in Neural Information Processing Systems, 12964-12976, 2019
1052019
Frank-Wolfe Bayesian quadrature: Probabilistic integration with theoretical guarantees
FX Briol, CJ Oates, M Girolami, MA Osborne
Advanced in Neural Information Processing Systems, 1162-1170, 2015
922015
Robust generalised Bayesian inference for intractable likelihoods
T Matsubara, J Knoblauch, FX Briol, C Oates
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2022
872022
Stein's method meets computational statistics: A review of some recent developments
A Anastasiou, A Barp, FX Briol, B Ebner, RE Gaunt, F Ghaderinezhad, ...
Statistical Science 38 (1), 120-139, 2022
832022
Statistical inference for generative models with maximum mean discrepancy
FX Briol, A Barp, AB Duncan, M Girolami
arXiv preprint arXiv:1906.05944, 2019
772019
Convergence rates for a class of estimators based on Stein’s method
CJ Oates, J Cockayne, FX Briol, M Girolami
Bernoulli 25 (2), 1141-1159, 2019
75*2019
Convergence guarantees for Gaussian process means with misspecified likelihoods and smoothness
G Wynne, FX Briol, M Girolami
Journal of Machine Learning Research 22 (123), 1-40, 2021
69*2021
Stein point Markov chain Monte Carlo
WY Chen, A Barp, FX Briol, J Gorham, M Girolami, L Mackey, C Oates
International Conference on Machine Learning, PMLR 97, 1011-1021, 2019
672019
Bayesian quadrature for multiple related integrals
X Xi, FX Briol, M Girolami
International Conference on Machine Learning, PMLR 80, 5369-5378, 2018
502018
Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap
C Dellaporta, J Knoblauch, T Damoulas, FX Briol
International Conference on Artificial Intelligence and Statistics, PMLR 151 …, 2022
432022
Geometry and dynamics for Markov chain Monte Carlo
A Barp, FX Briol, AD Kennedy, M Girolami
Annual Review of Statistics and Its Application 5 (1), 2018
402018
The ridgelet prior: A covariance function approach to prior specification for Bayesian neural networks
T Matsubara, CJ Oates, FX Briol
Journal of Machine Learning Research 22 (157), 1-57, 2021
252021
On the sampling problem for kernel quadrature
FX Briol, CJ Oates, J Cockayne, WY Chen, M Girolami
International Conference on Machine Learning, PMLR 70, 586--595, 2017
242017
Scalable control variates for Monte Carlo methods via stochastic optimization
S Si, C Oates, AB Duncan, L Carin, FX Briol
International Conference on Monte Carlo and Quasi-Monte Carlo Methods in …, 2020
222020
Generalized Bayesian inference for discrete intractable likelihood
T Matsubara, J Knoblauch, FX Briol, CJ Oates
Journal of the American Statistical Association, 1-11, 2023
202023
Probabilistic models for integration error in the assessment of functional cardiac models
CJ Oates, S Niederer, A Lee, FX Briol, M Girolami
Advances in Neural Information Processing Systems, 2017
202017
Robust and scalable Bayesian online changepoint detection
M Altamirano, FX Briol, J Knoblauch
International Conference on Machine Learning, PMLR 202, 642-663, 2023
192023
Composite goodness-of-fit tests with kernels
O Key, T Fernandez, A Gretton, FX Briol
arXiv preprint arXiv:2111.10275, 2021
182021
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