עקוב אחר
François-Xavier Briol
François-Xavier Briol
Associate Professor in Statistical Science, UCL
כתובת אימייל מאומתת בדומיין ucl.ac.uk - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
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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מאמרים 1–20